library(readr)
library(SciViews)
library(scatterplot3d)
library(car)
## Loading required package: carData
library(GGally)
## Loading required package: ggplot2
## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2
library(lattice)
library(ggplot2)
library(ggridges)
library(ggvis)
##
## Attaching package: 'ggvis'
## The following object is masked from 'package:ggplot2':
##
## resolution
library(ggthemes)
library(cowplot)
##
## Attaching package: 'cowplot'
## The following object is masked from 'package:ggthemes':
##
## theme_map
library(gapminder)
library(gganimate)
## No renderer backend detected. gganimate will default to writing frames to separate files
## Consider installing:
## - the `gifski` package for gif output
## - the `av` package for video output
## and restarting the R session
##
## Attaching package: 'gganimate'
## The following object is masked from 'package:ggvis':
##
## view_static
library(dplyr)
##
## Attaching package: 'dplyr'
## The following object is masked from 'package:car':
##
## recode
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tidyverse)
## ── Attaching packages
## ───────────────────────────────────────
## tidyverse 1.3.2 ──
## ✔ tibble 3.1.8 ✔ stringr 1.5.0
## ✔ tidyr 1.3.0 ✔ forcats 1.0.0
## ✔ purrr 1.0.1
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library(grid)
library(gridExtra)
##
## Attaching package: 'gridExtra'
##
## The following object is masked from 'package:dplyr':
##
## combine
library(RColorBrewer)
wholesale <- read_csv("/Users/rutwik/Desktop/RBS/Sem 2/Multivariate Analysis/Wholesale customers data.csv")
## Rows: 440 Columns: 7
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (1): Channel
## dbl (6): Fresh, Milk, Grocery, Frozen, Detergents_Paper, Delicassen
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
dim(wholesale)
## [1] 440 7
names(wholesale)
## [1] "Channel" "Fresh" "Milk" "Grocery"
## [5] "Frozen" "Detergents_Paper" "Delicassen"
str(wholesale)
## spc_tbl_ [440 × 7] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Channel : chr [1:440] "Retail" "Retail" "Retail" "Horeca" ...
## $ Fresh : num [1:440] 12669 7057 6353 13265 22615 ...
## $ Milk : num [1:440] 9656 9810 8808 1196 5410 ...
## $ Grocery : num [1:440] 7561 9568 7684 4221 7198 ...
## $ Frozen : num [1:440] 214 1762 2405 6404 3915 ...
## $ Detergents_Paper: num [1:440] 2674 3293 3516 507 1777 ...
## $ Delicassen : num [1:440] 1338 1776 7844 1788 5185 ...
## - attr(*, "spec")=
## .. cols(
## .. Channel = col_character(),
## .. Fresh = col_double(),
## .. Milk = col_double(),
## .. Grocery = col_double(),
## .. Frozen = col_double(),
## .. Detergents_Paper = col_double(),
## .. Delicassen = col_double()
## .. )
## - attr(*, "problems")=<externalptr>
var(wholesale)
## Warning in var(wholesale): NAs introduced by coercion
## Channel Fresh Milk Grocery Frozen Detergents_Paper
## Channel NA NA NA NA NA NA
## Fresh NA 159954927 9381789 -1424713 21236655 -6147825.7
## Milk NA 9381789 54469967 51083186 4442612 23288343.5
## Grocery NA -1424713 51083186 90310104 -1854282 41895189.7
## Frozen NA 21236655 4442612 -1854282 23567853 -3044324.9
## Detergents_Paper NA -6147826 23288343 41895190 -3044325 22732436.0
## Delicassen NA 8727310 8457925 5507291 5352342 931680.7
## Delicassen
## Channel NA
## Fresh 8727310.0
## Milk 8457924.8
## Grocery 5507291.3
## Frozen 5352341.8
## Detergents_Paper 931680.7
## Delicassen 7952997.5
# Since it forces NA, lets take the first column which is survivorship out
cov(wholesale[, c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 159954927 9381789 -1424713 21236655 -6147825.7
## Milk 9381789 54469967 51083186 4442612 23288343.5
## Grocery -1424713 51083186 90310104 -1854282 41895189.7
## Frozen 21236655 4442612 -1854282 23567853 -3044324.9
## Detergents_Paper -6147826 23288343 41895190 -3044325 22732436.0
## Delicassen 8727310 8457925 5507291 5352342 931680.7
## Delicassen
## Fresh 8727310.0
## Milk 8457924.8
## Grocery 5507291.3
## Frozen 5352341.8
## Detergents_Paper 931680.7
## Delicassen 7952997.5
#Taking a subset by survivorship of birds
cov(subset(wholesale, Channel == "Retail")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 80779016 20601490 9760788.2 4374357.2 1299662.1
## Milk 20601490 93695263 78210648.1 3060973.3 37873911.2
## Grocery 9760788 78210648 150487093.2 991647.7 71297033.1
## Frozen 4374357 3060973 991647.7 3286257.1 192021.0
## Detergents_Paper 1299662 37873911 71297033.1 192021.0 39577809.6
## Delicassen 4884133 6493880 3797502.0 1119771.4 840085.8
## Delicassen
## Fresh 4884133.3
## Milk 6493880.5
## Grocery 3797502.0
## Frozen 1119771.4
## Detergents_Paper 840085.8
## Delicassen 3817322.9
cov(subset(wholesale, Channel == "Horeca")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 191315579 14840389 11556901 26211464.1 -113871.0
## Milk 14840389 18941345 9298710 10043354.7 1200992.1
## Grocery 11556901 9298710 12570665 5176321.0 2145355.2
## Frozen 26211464 10043355 5176321 31853748.3 -194428.2
## Detergents_Paper -113871 1200992 2145355 -194428.2 1219022.8
## Delicassen 11080782 8624927 4986764 7608778.3 270277.7
## Delicassen
## Fresh 11080781.6
## Milk 8624927.4
## Grocery 4986763.8
## Frozen 7608778.3
## Detergents_Paper 270277.7
## Delicassen 9906296.2
# Take the correlation
cor(wholesale[, c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 1.00000000 0.1005098 -0.01185387 0.34588146 -0.1019529
## Milk 0.10050977 1.0000000 0.72833512 0.12399376 0.6618157
## Grocery -0.01185387 0.7283351 1.00000000 -0.04019274 0.9246407
## Frozen 0.34588146 0.1239938 -0.04019274 1.00000000 -0.1315249
## Detergents_Paper -0.10195294 0.6618157 0.92464069 -0.13152491 1.0000000
## Delicassen 0.24468997 0.4063683 0.20549651 0.39094747 0.0692913
## Delicassen
## Fresh 0.2446900
## Milk 0.4063683
## Grocery 0.2054965
## Frozen 0.3909475
## Detergents_Paper 0.0692913
## Delicassen 1.0000000
#Taking a subset by survivorship of birds
cor(subset(wholesale, Channel == "Retail")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 1.00000000 0.2368048 0.08852909 0.26848139 0.02298557
## Milk 0.23680482 1.0000000 0.65865416 0.17444156 0.62194998
## Grocery 0.08852909 0.6586542 1.00000000 0.04459201 0.92383828
## Frozen 0.26848139 0.1744416 0.04459201 1.00000000 0.01683728
## Detergents_Paper 0.02298557 0.6219500 0.92383828 0.01683728 1.00000000
## Delicassen 0.27813701 0.3433729 0.15844150 0.31615435 0.06834682
## Delicassen
## Fresh 0.27813701
## Milk 0.34337291
## Grocery 0.15844150
## Frozen 0.31615435
## Detergents_Paper 0.06834682
## Delicassen 1.00000000
cor(subset(wholesale, Channel == "Horeca")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 1.000000000 0.2465271 0.2356607 0.33576532 -0.007456451
## Milk 0.246527128 1.0000000 0.6026126 0.40887741 0.249936011
## Grocery 0.235660662 0.6026126 1.0000000 0.25867937 0.548042398
## Frozen 0.335765322 0.4088774 0.2586794 1.00000000 -0.031201333
## Detergents_Paper -0.007456451 0.2499360 0.5480424 -0.03120133 1.000000000
## Delicassen 0.254530348 0.6296430 0.4468729 0.42833050 0.077776542
## Delicassen
## Fresh 0.25453035
## Milk 0.62964300
## Grocery 0.44687289
## Frozen 0.42833050
## Detergents_Paper 0.07777654
## Delicassen 1.00000000
#column means
#For Retail
colMeans(subset(wholesale, Channel == "Retail")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen
## 8904.324 10716.500 16322.852 1652.613
## Detergents_Paper Delicassen
## 7269.507 1753.437
#For Horeca
colMeans(subset(wholesale, Channel == "Horeca")[,c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen
## 13475.5604 3451.7248 3962.1376 3748.2517
## Detergents_Paper Delicassen
## 790.5604 1415.9564
# ggplot
#Using ggplot to plot different variables against Channel of the annual spending
ggplot(wholesale, aes(x=Channel,y=Fresh)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Channel,y=Milk)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Channel,y=Grocery)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Channel,y=Frozen)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Channel,y=Detergents_Paper)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Channel,y=Delicassen)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Fresh, y=Milk)) + geom_point(aes(color=Channel))
ggplot(wholesale, aes(x=Fresh,y=Milk)) + xlim(0,100000) + geom_point(aes(color=Channel), pch=17) +
labs(x="Annual spending (m.u.) on Fresh products (Continuous)", y="Annual spending (m.u.) on Milk products (Continuous);", title="Wholesale Customer Data")
## Warning: Removed 1 rows containing missing values (`geom_point()`).
# bar chart
ggplot(wholesale, aes(Fresh)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Milk)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Grocery)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Frozen)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Detergents_Paper)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Delicassen)) + geom_bar(position="stack",aes(color=Channel))
ggplot(wholesale, aes(Fresh)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
ggplot(wholesale, aes(Milk)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
ggplot(wholesale, aes(Grocery)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
ggplot(wholesale, aes(Frozen)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
ggplot(wholesale, aes(Detergents_Paper)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
ggplot(wholesale, aes(Delicassen)) + facet_grid(.~Channel) + geom_bar(position="dodge",aes(color=Channel))
# histogram
ggplot(wholesale, aes(Fresh))+geom_histogram(aes(color=Channel))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot(wholesale, aes(Milk))+geom_histogram(aes(fill = after_stat(count)))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot(wholesale, aes(Grocery))+geom_histogram(aes(fill = after_stat(count)))
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
# violin plot
ggplot(wholesale, aes(x=Channel, y=Fresh)) + geom_violin(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Milk)) + geom_violin(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Grocery)) + geom_violin(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Frozen)) + geom_violin(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Detergents_Paper)) + geom_violin(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Delicassen)) + geom_violin(aes(color=Channel))
# box plot
ggplot(wholesale, aes(x=Channel, y=Fresh)) + geom_boxplot(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Milk)) + geom_boxplot(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Grocery)) + geom_boxplot(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Frozen)) + geom_boxplot(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Detergents_Paper)) + geom_boxplot(aes(color=Channel))
ggplot(wholesale, aes(x=Channel, y=Delicassen)) + geom_boxplot(aes(color=Channel))
# density plot and ggridges
ggplot(wholesale, aes(x=Fresh, fill=Channel, color=Channel)) + geom_density(alpha=0.3, aes(y=..scaled..))
## Warning: The dot-dot notation (`..scaled..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(scaled)` instead.
# hexbin
ggplot(wholesale, aes(x=Fresh, y=Channel)) + geom_hex(aes(color=Channel))
cor(wholesale[, c("Fresh", "Milk", "Grocery", "Frozen", "Detergents_Paper","Delicassen")])
## Fresh Milk Grocery Frozen Detergents_Paper
## Fresh 1.00000000 0.1005098 -0.01185387 0.34588146 -0.1019529
## Milk 0.10050977 1.0000000 0.72833512 0.12399376 0.6618157
## Grocery -0.01185387 0.7283351 1.00000000 -0.04019274 0.9246407
## Frozen 0.34588146 0.1239938 -0.04019274 1.00000000 -0.1315249
## Detergents_Paper -0.10195294 0.6618157 0.92464069 -0.13152491 1.0000000
## Delicassen 0.24468997 0.4063683 0.20549651 0.39094747 0.0692913
## Delicassen
## Fresh 0.2446900
## Milk 0.4063683
## Grocery 0.2054965
## Frozen 0.3909475
## Detergents_Paper 0.0692913
## Delicassen 1.0000000
wholesale_data <- wholesale[,-c(1:2)]
# Using prcomp to compute the principal components (eigenvalues and eigenvectors). With scale=TRUE, variable means are set to zero, and variances set to one
wholesale_pca <- prcomp(wholesale_data,scale=TRUE)
wholesale_pca
## Standard deviations (1, .., p=5):
## [1] 1.6254958 1.1958226 0.7594873 0.5356839 0.2529693
##
## Rotation (n x k) = (5 x 5):
## PC1 PC2 PC3 PC4 PC5
## Milk -0.54363795 0.1146154 0.09014458 -0.82543534 -0.04302952
## Grocery -0.58193330 -0.1556719 -0.12777739 0.30993371 0.72438520
## Frozen -0.03962544 0.7024176 -0.70857828 0.04761674 -0.02624427
## Detergents_Paper -0.55369302 -0.2718776 -0.19028739 0.34173928 -0.68301653
## Delicassen -0.24013597 0.6287461 0.66125216 0.32178331 -0.07883018
summary(wholesale_pca)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5
## Standard deviation 1.6255 1.1958 0.7595 0.53568 0.2530
## Proportion of Variance 0.5284 0.2860 0.1154 0.05739 0.0128
## Cumulative Proportion 0.5284 0.8145 0.9298 0.98720 1.0000
# sample scores stored in sparrows_pca$x
# singular values (square roots of eigenvalues) stored in sparrow_pca$sdev
# loadings (eigenvectors) are stored in sparrows_pca$rotation
# variable means stored in sparrows_pca$center
# variable standard deviations stored in sparrows_pca$scale
# A table containing eigenvalues and %'s accounted, follows
# Eigenvalues are sdev^2
(eigen_wholesale <- wholesale_pca$sdev^2)
## [1] 2.64223659 1.42999181 0.57682096 0.28695719 0.06399345
names(eigen_wholesale) <- paste("PC",1:5,sep="")
eigen_wholesale
## PC1 PC2 PC3 PC4 PC5
## 2.64223659 1.42999181 0.57682096 0.28695719 0.06399345
sumlambdas <- sum(eigen_wholesale)
sumlambdas
## [1] 5
propvar <- eigen_wholesale/sumlambdas
propvar
## PC1 PC2 PC3 PC4 PC5
## 0.52844732 0.28599836 0.11536419 0.05739144 0.01279869
cumvar_wholesale <- cumsum(propvar)
cumvar_wholesale
## PC1 PC2 PC3 PC4 PC5
## 0.5284473 0.8144457 0.9298099 0.9872013 1.0000000
matlambdas <- rbind(eigen_wholesale,propvar,cumvar_wholesale)
rownames(matlambdas) <- c("Eigenvalues","Prop. variance","Cum. prop. variance")
round(matlambdas,3)
## PC1 PC2 PC3 PC4 PC5
## Eigenvalues 2.642 1.430 0.577 0.287 0.064
## Prop. variance 0.528 0.286 0.115 0.057 0.013
## Cum. prop. variance 0.528 0.814 0.930 0.987 1.000
summary(wholesale_pca)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5
## Standard deviation 1.6255 1.1958 0.7595 0.53568 0.2530
## Proportion of Variance 0.5284 0.2860 0.1154 0.05739 0.0128
## Cumulative Proportion 0.5284 0.8145 0.9298 0.98720 1.0000
wholesale_pca$rotation
## PC1 PC2 PC3 PC4 PC5
## Milk -0.54363795 0.1146154 0.09014458 -0.82543534 -0.04302952
## Grocery -0.58193330 -0.1556719 -0.12777739 0.30993371 0.72438520
## Frozen -0.03962544 0.7024176 -0.70857828 0.04761674 -0.02624427
## Detergents_Paper -0.55369302 -0.2718776 -0.19028739 0.34173928 -0.68301653
## Delicassen -0.24013597 0.6287461 0.66125216 0.32178331 -0.07883018
print(wholesale_pca)
## Standard deviations (1, .., p=5):
## [1] 1.6254958 1.1958226 0.7594873 0.5356839 0.2529693
##
## Rotation (n x k) = (5 x 5):
## PC1 PC2 PC3 PC4 PC5
## Milk -0.54363795 0.1146154 0.09014458 -0.82543534 -0.04302952
## Grocery -0.58193330 -0.1556719 -0.12777739 0.30993371 0.72438520
## Frozen -0.03962544 0.7024176 -0.70857828 0.04761674 -0.02624427
## Detergents_Paper -0.55369302 -0.2718776 -0.19028739 0.34173928 -0.68301653
## Delicassen -0.24013597 0.6287461 0.66125216 0.32178331 -0.07883018
## Sample scores stored in sparrow_pca$x
wholesale_pca$x
## PC1 PC2 PC3 PC4 PC5
## [1,] -0.19707283 -0.3770084356 0.4339928374 -5.086349e-01 -0.001854585
## [2,] -0.45313294 -0.1211597823 0.2609418663 -3.508749e-01 0.040946165
## [3,] -0.81180172 1.3273282020 1.5940953009 4.144155e-01 -0.301861199
## [4,] 0.79342916 0.6658443374 -0.3359082992 2.853570e-01 0.057266232
## [5,] -0.11570147 1.0073354473 0.7846578714 3.653701e-01 -0.003812347
## [6,] 0.14370629 -0.2180994333 0.4452745197 -4.774821e-01 -0.059000770
## [7,] 0.32567049 -0.6325704892 0.1196417115 1.399425e-01 -0.054904769
## [8,] -0.15665440 -0.0331363080 0.4012580200 2.786108e-01 0.032831032
## [9,] 0.48890741 -0.4938233270 0.2485820432 -1.502553e-02 0.081354092
## [10,] -1.62027497 -0.5048683883 0.1499964109 1.363545e-01 0.145687282
## [11,] -0.66758413 -0.0238881161 -0.3383420998 4.676957e-01 -0.071596678
## [12,] 0.92597350 -0.3515756476 0.0822191593 1.100768e-01 0.137720104
## [13,] -0.92658585 -0.1074909163 0.7247966859 -4.006276e-01 0.084630659
## [14,] -0.82672223 -0.5293360636 -0.4619419906 3.523687e-01 0.011172418
## [15,] -0.80858534 -0.3934991730 0.4585439002 -7.316764e-02 -0.020590692
## [16,] 0.93709140 -0.5308636604 0.2043574976 9.831297e-02 0.032723673
## [17,] -0.60479469 -0.6384278916 0.2404058097 -1.647392e-01 0.095547612
## [18,] 0.33914993 0.5663431002 1.1904730227 -6.896284e-02 -0.095319576
## [19,] -0.29126066 0.2233895662 0.4970352941 1.829471e-01 0.135411974
## [20,] 0.29954840 -0.6312712075 0.0644977021 2.521058e-01 0.228237979
## [21,] 0.33682556 -0.0861339420 0.4875413015 3.768933e-02 -0.164582644
## [22,] 1.09654804 -0.0043401285 -0.1497704508 7.141227e-02 -0.040058284
## [23,] 0.26619036 1.5683970175 -0.2467060883 6.670989e-01 -0.283900004
## [24,] -4.58054505 3.8072871727 3.3396697767 -1.130469e+00 0.254755186
## [25,] -1.19755447 0.8003953225 0.9263685687 3.438610e-01 0.074691495
## [26,] 0.15537156 -0.8250948908 0.0157524281 4.829123e-02 -0.122135167
## [27,] 1.03266607 0.0159926101 -0.0590410608 1.074156e-01 0.037212525
## [28,] 1.09811094 -0.4373483299 0.2574858397 5.881782e-02 0.095718884
## [29,] -3.14687957 0.1506165427 0.8514050232 -2.440491e-01 0.374539040
## [30,] 0.88052223 -0.2960335906 0.2061557803 1.353125e-02 -0.101725549
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## [425,] 0.04046836 -0.7367264203 -0.0847164943 3.219454e-01 0.343336774
## [426,] 0.76883248 2.0500342258 -1.5657601158 1.670196e-01 -0.067827419
## [427,] -0.93848842 -0.0821362098 -0.0534415939 1.076078e-02 0.138959378
## [428,] -0.43132555 2.0067711242 -1.5734003459 -1.398859e+00 0.039329073
## [429,] 0.51934102 -0.2273851246 -0.0315692426 -4.106207e-01 0.096672075
## [430,] 0.83217183 -0.0517546591 0.7913966759 1.911758e-01 0.080207639
## [431,] -0.12732308 -0.2510251070 0.4661498794 3.030175e-01 1.035711609
## [432,] 0.28430937 1.6278170123 -1.4322862099 -6.732602e-02 -0.051096480
## [433,] 0.83664364 -0.5884685158 0.1925679473 1.462679e-01 0.052584928
## [434,] 0.89763536 -0.0286593561 0.3618008079 -1.269600e-01 -0.105069502
## [435,] 0.27267232 -0.4987640539 0.1838051451 7.266804e-02 0.119401988
## [436,] -0.78171970 1.7262064236 -1.2339946527 -4.534560e-01 0.892440952
## [437,] 1.00383404 0.6000966110 0.1372499975 1.617472e-01 -0.153667550
## [438,] -3.47543102 -1.2015869428 -0.1938524404 5.134742e-01 -0.065875377
## [439,] 0.91187529 0.0286815529 0.5761825595 9.421507e-02 -0.030771798
## [440,] 1.06427400 -0.6008476585 0.2126003922 -8.899895e-02 0.011009682
attach(wholesale)
# Identifying the scores by their Channel status
wholesale_channel_pca <- cbind(data.frame(Channel),wholesale_pca$x)
wholesale_channel_pca
## Channel PC1 PC2 PC3 PC4 PC5
## 1 Retail -0.19707283 -0.3770084356 0.4339928374 -5.086349e-01 -0.001854585
## 2 Retail -0.45313294 -0.1211597823 0.2609418663 -3.508749e-01 0.040946165
## 3 Retail -0.81180172 1.3273282020 1.5940953009 4.144155e-01 -0.301861199
## 4 Horeca 0.79342916 0.6658443374 -0.3359082992 2.853570e-01 0.057266232
## 5 Retail -0.11570147 1.0073354473 0.7846578714 3.653701e-01 -0.003812347
## 6 Retail 0.14370629 -0.2180994333 0.4452745197 -4.774821e-01 -0.059000770
## 7 Retail 0.32567049 -0.6325704892 0.1196417115 1.399425e-01 -0.054904769
## 8 Retail -0.15665440 -0.0331363080 0.4012580200 2.786108e-01 0.032831032
## 9 Horeca 0.48890741 -0.4938233270 0.2485820432 -1.502553e-02 0.081354092
## 10 Retail -1.62027497 -0.5048683883 0.1499964109 1.363545e-01 0.145687282
## 11 Retail -0.66758413 -0.0238881161 -0.3383420998 4.676957e-01 -0.071596678
## 12 Retail 0.92597350 -0.3515756476 0.0822191593 1.100768e-01 0.137720104
## 13 Retail -0.92658585 -0.1074909163 0.7247966859 -4.006276e-01 0.084630659
## 14 Retail -0.82672223 -0.5293360636 -0.4619419906 3.523687e-01 0.011172418
## 15 Retail -0.80858534 -0.3934991730 0.4585439002 -7.316764e-02 -0.020590692
## 16 Horeca 0.93709140 -0.5308636604 0.2043574976 9.831297e-02 0.032723673
## 17 Retail -0.60479469 -0.6384278916 0.2404058097 -1.647392e-01 0.095547612
## 18 Horeca 0.33914993 0.5663431002 1.1904730227 -6.896284e-02 -0.095319576
## 19 Retail -0.29126066 0.2233895662 0.4970352941 1.829471e-01 0.135411974
## 20 Horeca 0.29954840 -0.6312712075 0.0644977021 2.521058e-01 0.228237979
## 21 Retail 0.33682556 -0.0861339420 0.4875413015 3.768933e-02 -0.164582644
## 22 Horeca 1.09654804 -0.0043401285 -0.1497704508 7.141227e-02 -0.040058284
## 23 Horeca 0.26619036 1.5683970175 -0.2467060883 6.670989e-01 -0.283900004
## 24 Retail -4.58054505 3.8072871727 3.3396697767 -1.130469e+00 0.254755186
## 25 Retail -1.19755447 0.8003953225 0.9263685687 3.438610e-01 0.074691495
## 26 Retail 0.15537156 -0.8250948908 0.0157524281 4.829123e-02 -0.122135167
## 27 Horeca 1.03266607 0.0159926101 -0.0590410608 1.074156e-01 0.037212525
## 28 Horeca 1.09811094 -0.4373483299 0.2574858397 5.881782e-02 0.095718884
## 29 Retail -3.14687957 0.1506165427 0.8514050232 -2.440491e-01 0.374539040
## 30 Horeca 0.88052223 -0.2960335906 0.2061557803 1.353125e-02 -0.101725549
## 31 Horeca -0.05215116 -0.0007608697 0.5787210362 4.390835e-01 0.330576240
## 32 Horeca 0.69579690 -0.0888786625 0.1462865658 -2.131695e-01 -0.043052084
## 33 Horeca 0.98632753 -0.5302711469 0.2387360039 3.962267e-02 -0.032243165
## 34 Horeca 0.41807632 0.4822328908 -0.4532962679 -1.084847e-01 0.315119579
## 35 Horeca 1.02591988 -0.4642031406 0.2470086458 -8.541622e-02 -0.021926123
## 36 Retail -0.21643153 -0.7002955975 -0.0286492746 8.763578e-02 0.089179114
## 37 Horeca 0.24158323 0.6313110592 1.0201656795 2.740459e-01 0.025899292
## 38 Retail -0.97020398 -0.5543555171 -0.1693693299 -2.287695e-01 -0.173107471
## 39 Retail -1.62332525 -0.9046825507 0.0284863528 -6.876237e-01 0.072911071
## 40 Horeca 0.95272626 1.4991601790 -0.5480032712 3.916575e-01 -0.200711189
## 41 Horeca 0.08308879 2.0275377344 0.1721111919 4.933808e-01 -0.142283907
## 42 Horeca 0.25869103 0.1421617102 0.4567992931 3.539627e-01 -0.122343929
## 43 Retail -0.87588116 -1.0635936007 -0.1589398770 1.228399e-01 0.005470463
## 44 Retail -2.00255094 -1.2141592087 -0.4235084566 2.189990e-01 0.292958699
## 45 Retail -0.30164586 -0.8128614625 -0.0610496539 -1.224052e-01 -0.009380470
## 46 Retail -2.83141245 0.3536181366 0.8431308911 -6.720454e-01 0.210311577
## 47 Retail -1.90336183 -0.5432914831 -0.0554886874 -2.103213e-01 0.468640242
## 48 Retail -9.41725404 0.5414621846 -0.4271519661 -1.731283e+00 0.133925231
## 49 Retail -0.44041724 -0.5408300715 0.2274220164 1.858785e-01 -0.085748415
## 50 Retail -3.63590895 -0.9762339518 -0.4172346295 -3.493400e-01 -0.008648759
## 51 Horeca 0.91517116 0.4104644981 0.1479309633 2.485985e-01 -0.124280227
## 52 Horeca 0.47041131 -0.6176023581 0.1716656472 -9.969138e-02 0.179345625
## 53 Retail 0.34153413 -0.4009520531 0.3295290114 6.842046e-02 -0.084407972
## 54 Retail -0.75096260 -0.7685290601 -0.0652044882 -3.819017e-01 -0.096389717
## 55 Horeca 1.02036283 0.0487333009 0.1823242891 7.034276e-02 -0.039970438
## 56 Horeca 0.48573185 -0.3152336743 0.2495333559 1.398177e-02 -0.067490936
## 57 Retail -4.63920836 -0.8901055110 -0.5298270393 -1.038605e+00 -0.819611828
## 58 Retail -0.95925425 -0.7378871248 0.2151100896 -1.012359e-01 -0.479576833
## 59 Horeca 1.08902399 -0.4058042205 0.2500262845 -1.164280e-01 -0.034073572
## 60 Horeca 0.02055344 -0.4281666899 0.4332603258 4.625049e-02 -0.005978029
## 61 Retail 0.20266611 -0.8307229912 0.0488423661 2.140045e-01 -0.112791726
## 62 Retail -8.37149191 -1.5623789638 -1.1584129243 -1.933842e-01 0.319907948
## 63 Retail -0.04643766 -0.0064623816 -0.3126388497 -6.399385e-02 -0.270890553
## 64 Retail -1.44256223 -0.3881746020 -0.2539083496 -7.828486e-02 -0.117075631
## 65 Horeca 0.84129649 0.1089106750 -0.1116094122 2.036070e-01 -0.090476223
## 66 Retail -5.88216805 -2.0643796924 -0.7569200156 1.028312e+00 -0.240375986
## 67 Horeca 0.42975520 -0.8439903706 0.0033292780 3.019871e-01 -0.042364665
## 68 Retail -0.59711484 -0.6209401671 -0.0494590712 1.373610e-01 0.119889933
## 69 Horeca 0.22115034 0.9618614565 0.1144127302 -2.362520e-01 -0.069370103
## 70 Horeca 1.02170230 -0.4498752241 0.1528820924 -2.238458e-01 -0.120372633
## 71 Horeca 0.84070633 1.2369213016 -1.0142299556 1.233516e-01 0.019609630
## 72 Horeca -1.73915275 2.8610779436 2.4170622052 2.526060e+00 0.464898413
## 73 Horeca 0.62067938 0.7050255622 -1.0362899361 -3.073257e-01 -0.169665352
## 74 Retail 0.26682334 0.6376948170 -0.8755662868 -1.254282e-01 0.361266482
## 75 Retail -0.04638691 -0.1674522707 0.3416721379 -5.974311e-02 0.280263771
## 76 Horeca 1.20012549 0.2925598478 -0.1589521213 5.912953e-03 -0.158188044
## 77 Horeca 0.54017219 0.6274661824 -0.7126274387 3.926234e-03 0.235234832
## 78 Retail -2.77004981 -1.1857563171 -0.3572508458 4.752266e-01 0.244348076
## 79 Horeca 1.12399443 -0.2721741808 -0.0502825534 -2.452565e-02 -0.008690418
## 80 Horeca 0.65209963 -0.1635736239 0.4455307307 1.627898e-02 -0.063766052
## 81 Horeca 1.03868601 -0.4709420234 0.2485400502 9.200612e-02 0.019753232
## 82 Retail -1.10479248 -1.0377605203 -0.1519433582 -3.801156e-02 -0.183875803
## 83 Retail -0.56696336 -0.1897705085 0.5070899455 -1.672162e-01 0.108922971
## 84 Horeca 1.03054389 -0.1083993421 0.0575018685 1.189421e-02 -0.086393476
## 85 Retail 0.39812160 -0.6286896384 -0.0790878932 6.345882e-02 -0.312116534
## 86 Retail -12.68123458 -2.9055675082 -1.5301790149 1.109718e+00 0.766109027
## 87 Retail -8.39266413 -0.7648749958 -0.0254756094 -5.643262e+00 -0.986574914
## 88 Horeca -0.92068706 3.3879831694 2.5748630597 1.493591e+00 -0.172326436
## 89 Horeca 1.01342557 0.7716998749 -1.2224864249 1.620546e-01 0.127114509
## 90 Horeca 0.44301966 0.5731766717 0.4416464506 1.520250e-01 0.111153688
## 91 Horeca 1.19321062 -0.0368736054 -0.1796662555 4.390303e-02 -0.016938275
## 92 Horeca 0.80614475 0.8926142932 -0.7902658775 9.552051e-03 -0.091570032
## 93 Retail -5.24057761 -0.1447202035 0.1233521218 -7.733263e-02 -0.687874557
## 94 Horeca 0.52578694 5.0971997130 -4.2280974876 3.562690e-01 -0.235963847
## 95 Retail -0.79761716 -0.7786843800 0.0650273452 -6.281708e-01 -0.038072173
## 96 Horeca 0.71560919 -0.4279470962 0.2866668376 -4.319073e-02 0.305115990
## 97 Retail 0.24404605 -0.8238016100 0.0398452920 2.543221e-01 -0.058548989
## 98 Horeca 1.32938626 -0.4629908981 0.1364874089 -1.157487e-02 -0.068943918
## 99 Horeca 1.32246301 -0.4351711891 0.1309323486 1.898908e-02 -0.058179488
## 100 Horeca 1.02727861 0.2983698332 -0.5129768013 -9.591612e-02 -0.037799311
## 101 Retail -1.13082005 0.0296427973 0.0885664798 4.577611e-01 -0.473247863
## 102 Retail -1.34423210 -0.4240373165 0.0836781087 1.010917e-02 0.047409545
## 103 Retail -0.21246138 -0.1865573632 -0.0137137578 1.731627e-02 -0.260442905
## 104 Horeca 0.06820127 2.4096180816 -1.9396808134 4.447883e-01 0.178855067
## 105 Horeca 0.80468449 -0.3727619490 0.0956486645 3.469641e-02 -0.086245320
## 106 Horeca 0.94469735 -0.1982170834 0.3856879072 1.704796e-01 0.133073495
## 107 Retail -0.66901612 -0.6188300049 0.3127463650 3.184159e-01 -0.351635129
## 108 Retail -1.47652662 -0.4917273047 -0.2096213973 1.042837e-01 -0.366056895
## 109 Retail -0.04077613 -0.3953887590 0.4044253759 -4.101700e-01 -0.011842382
## 110 Retail -1.70666698 -0.7445501815 -0.0743597119 -8.805089e-01 1.888181050
## 111 Horeca 0.99983015 0.1048203863 0.2865328374 7.158538e-02 -0.063314112
## 112 Retail -1.37687414 -0.6081606384 0.1224336064 -4.770345e-02 0.202325530
## 113 Horeca 0.68923179 1.2798147189 -0.4339000015 1.794542e-01 -0.120975838
## 114 Horeca 0.90109151 0.2079202525 0.1193587893 2.975898e-02 -0.126406650
## 115 Horeca 1.05901888 0.0493188652 0.1474579566 1.006991e-01 -0.020229691
## 116 Horeca 1.05586310 -0.1034380740 -0.0528084643 1.030625e-01 0.051592527
## 117 Horeca 0.94497402 -0.3443957553 0.0458862013 -1.318167e-01 0.081944110
## 118 Horeca 0.63888952 -0.1290378910 0.2358638727 -1.088179e-01 0.200165919
## 119 Horeca 0.94868598 0.3684258484 -0.3442094906 3.215203e-02 -0.045101450
## 120 Horeca 0.98250864 0.1114467083 -0.1886718345 -8.411286e-02 -0.027206760
## 121 Horeca 0.96940760 -0.0240916571 0.1173633154 1.211556e-01 0.083059013
## 122 Horeca 1.00153477 -0.1658860503 -0.0390138016 -2.630435e-01 -0.062843175
## 123 Horeca 1.28120984 -0.1024026325 0.1511531050 8.324730e-02 -0.121160465
## 124 Retail -0.18913115 -0.3203897860 -0.1106006465 -7.592123e-01 0.209858651
## 125 Horeca 0.86596557 0.4226150095 -0.1163835099 1.589650e-01 -0.026966052
## 126 Horeca 0.40917867 1.9108688107 -2.0407836107 1.442061e-01 0.194309814
## 127 Horeca 1.01779186 0.6950263922 -0.8546792729 -1.292082e-02 -0.092424266
## 128 Retail -0.30277111 -0.0382865069 0.6076499875 1.001440e-02 0.248558255
## 129 Horeca 0.39288434 -0.5444758971 0.2361887980 -8.086403e-01 -0.013436955
## 130 Horeca 1.02620109 0.0404906424 0.3923445875 1.777608e-01 -0.109445886
## 131 Horeca 1.00675513 0.5407968338 -0.4618272530 -7.625720e-02 -0.177348616
## 132 Horeca 1.30343896 -0.4607099296 0.2643065329 -3.356327e-02 -0.100342543
## 133 Horeca 0.95838681 -0.4869393345 0.1881508451 -5.659957e-02 -0.072253726
## 134 Horeca 1.18401500 -0.4471723939 0.2570614765 -3.016307e-02 -0.062315609
## 135 Horeca 1.07458712 -0.3650636260 0.2546463208 -8.959202e-02 0.028826429
## 136 Horeca 1.08937421 -0.3717038493 0.1205741859 -1.843713e-02 0.045760580
## 137 Horeca -0.11183011 0.3043792045 -0.1516516077 -3.557179e-01 -0.032810349
## 138 Horeca 0.20888553 -0.5275345677 0.1124609346 -5.930183e-01 0.376046862
## 139 Horeca 0.47286002 0.1412503836 0.9606664322 5.895386e-02 0.130678757
## 140 Horeca 0.67212442 -0.2671718542 0.3297977543 -3.097939e-01 0.003832633
## 141 Horeca 0.28796809 0.2251490753 0.4384379673 1.275042e-01 0.208626132
## 142 Horeca -0.02250288 -0.0922838655 0.6251372899 -1.162354e+00 0.168419794
## 143 Horeca 0.34418432 -0.1711513228 -0.2189102391 -5.212920e-01 0.467973078
## 144 Horeca 1.07654549 0.6940836506 -0.9243576757 -1.694764e-02 -0.137634393
## 145 Horeca 0.93281684 -0.5228990290 0.2694356743 -3.070418e-01 -0.050356643
## 146 Retail -3.18443785 -0.7438540221 0.4066323700 1.583661e+00 0.575108123
## 147 Horeca 1.06717252 -0.3397410076 0.2201744068 -9.358929e-02 0.024377222
## 148 Horeca 0.80824332 -0.3302172553 0.1391921066 -1.604844e-01 -0.090258890
## 149 Horeca 1.22430136 0.0871948598 -0.2591661155 4.019766e-02 -0.136947866
## 150 Horeca 1.05447741 -0.1543326372 0.4536170345 5.211853e-02 -0.043550579
## 151 Horeca 1.04333128 -0.2288550227 0.3594012592 -2.596068e-02 -0.035171898
## 152 Horeca 0.84943798 -0.1035340420 0.5836853316 -1.020722e-01 -0.054543391
## 153 Horeca 1.02940017 -0.1547998275 -0.1923899590 2.856667e-03 0.058902303
## 154 Horeca 0.39707127 -0.0168057926 0.5788233217 -7.640874e-01 -0.066660671
## 155 Horeca 1.38885601 -0.5690528884 0.2314207961 -2.124517e-02 -0.091789299
## 156 Retail -2.10534411 -0.8790908783 0.1196340531 4.951007e-01 -0.399152538
## 157 Retail -0.94690511 -0.3674869252 0.5395080461 7.169925e-01 -0.048400289
## 158 Horeca 0.99393880 -0.0635048487 -0.2020406424 4.515528e-02 -0.065786576
## 159 Retail -0.28531006 -0.3541772263 0.2917156994 4.519864e-02 -0.031081093
## 160 Retail -1.03017136 -1.0361993602 -0.1707735459 2.128945e-01 -0.193738153
## 161 Retail -0.35485260 -0.3853783711 0.3230685951 5.594227e-01 0.157293084
## 162 Horeca 1.14689210 0.0795306282 0.6088149730 1.928414e-01 -0.150608121
## 163 Horeca 0.92036981 -0.1025116285 -0.0397713887 -1.145054e-02 0.113646494
## 164 Retail -3.05168162 -1.1166208170 -0.7159845011 1.537208e-01 -0.135355954
## 165 Retail -0.14994267 -0.3913717078 -0.2421719977 -2.766832e-01 -0.036986765
## 166 Retail -1.80878413 0.0566334496 -0.2422449984 3.512095e-02 0.230965549
## 167 Retail -0.54851470 0.0452361851 0.7101191669 3.068431e-01 -0.259912693
## 168 Horeca 0.71052625 -0.4665092314 0.2733552116 -6.900412e-02 -0.132030137
## 169 Horeca 1.24301618 -0.2889456013 0.1342404677 -9.451263e-03 -0.074195145
## 170 Horeca 1.12716773 -0.0936776748 0.0446746742 8.243335e-02 0.015988183
## 171 Retail -0.90926104 -0.8317067060 -0.1998028894 -3.331411e-03 -0.147138197
## 172 Retail -3.27135965 0.4844985168 1.3117135113 -9.195516e-01 -0.175570118
## 173 Horeca 0.20685284 -0.5580156466 0.2248068955 -1.338342e-01 -0.062418192
## 174 Retail -1.58573375 -1.0507762119 -0.2920206050 5.614834e-01 -0.069519512
## 175 Horeca 0.83240063 0.0296716850 0.1511531426 2.142830e-01 0.216354135
## 176 Retail -0.53378209 -0.5059735509 0.4009604478 -1.696169e-02 0.110272790
## 177 Horeca 0.23300367 0.4510780875 -0.8435857968 -3.784251e-01 0.091638181
## 178 Horeca 0.34523774 0.2986179690 0.6309155013 -3.748515e-01 0.116635082
## 179 Horeca 0.52247477 -0.3031257221 0.1815526848 -5.867474e-01 0.200947639
## 180 Horeca 0.63766473 0.5699523520 0.1113244841 -1.763475e-01 -0.062042887
## 181 Horeca 0.01290303 -0.0294551255 0.7374726259 1.485187e-02 0.263695260
## 182 Horeca -3.32956183 3.6298166964 -0.2769640395 -1.248901e+00 0.071987331
## 183 Horeca -0.68822721 -0.9146602969 -0.0990009318 -1.158184e-01 -0.344501680
## 184 Horeca -7.47744667 15.7336154455 6.4071500330 1.566581e+00 -0.390933851
## 185 Horeca 1.00703448 -0.6486837093 0.1682726870 5.514838e-02 0.204836624
## 186 Horeca 0.81312626 -0.1310929456 0.0426500561 -6.519887e-01 -0.078055731
## 187 Horeca 1.11229463 0.0242439747 -0.1370615402 1.328789e-01 -0.213249552
## 188 Horeca -0.24041783 0.0940055884 -0.8447029159 -2.866790e-01 0.072035440
## 189 Retail -0.72607631 -0.5535689471 -0.4026667470 6.842392e-02 -0.259887453
## 190 Retail -0.78285913 -0.3648986302 0.4627545482 -4.376192e-01 0.080242773
## 191 Horeca 0.74272114 0.5531106755 -0.7682232617 -5.684404e-01 -0.044045398
## 192 Horeca 1.27769586 -0.4528908326 0.1150534175 1.173032e-02 -0.010051253
## 193 Horeca 1.09693599 -0.4344151638 0.2381189714 -4.626280e-02 0.021607927
## 194 Retail -0.81285702 -0.8912956579 -0.1963626901 7.383901e-01 0.597568986
## 195 Horeca 1.00169591 -0.2619137189 0.3502776810 1.257535e-01 0.033380504
## 196 Horeca 0.45245343 0.9280037294 -0.5185901798 -1.246246e-01 0.129445254
## 197 Horeca 0.08628883 2.7568111298 -1.8229643830 -1.018957e-01 -0.059879885
## 198 Retail -0.39085008 -0.3955405972 0.1964547248 1.120201e-02 -0.014723123
## 199 Horeca 0.66997842 -0.0262749566 -0.1984931057 1.164929e-01 0.283969333
## 200 Horeca 1.02565202 -0.4494088678 0.2308137614 -1.343236e-01 -0.022683101
## 201 Retail -2.23900996 -0.5878260801 -0.7085900734 8.764202e-02 0.116989345
## 202 Retail -2.99546346 -0.6844705504 -0.6063795435 4.206181e-01 -0.406247403
## 203 Horeca -0.68180673 1.6877976045 1.1111432584 -1.448361e-01 0.296475108
## 204 Horeca 1.10109815 -0.5880892539 0.1182040110 4.898085e-02 -0.075060624
## 205 Horeca 0.89280368 -0.1557704566 0.2918836756 2.145287e-01 0.247566809
## 206 Retail -2.04834810 -1.0164029887 -0.2749671288 1.925170e-01 0.277801549
## 207 Horeca 1.22289397 -0.4091923864 0.1658758384 -1.619192e-02 -0.086383217
## 208 Retail 0.02999763 -0.4562055716 -0.3960906986 7.069393e-02 -0.444580597
## 209 Horeca 0.29338844 -0.3614455997 -0.0080606821 1.020401e-01 -0.194049088
## 210 Retail -2.07821189 -1.0624050684 -0.2629478297 9.111398e-02 -0.702586793
## 211 Horeca 0.95666185 0.1415798527 0.4661520779 8.654914e-02 -0.108537036
## 212 Retail -5.65091274 -0.5719339518 -0.7387671291 -1.300213e-01 -0.126122041
## 213 Horeca 1.01303835 -0.0291142686 0.4447647467 1.647516e-01 -0.039979160
## 214 Horeca -0.07733767 -0.3524530076 0.1631543516 -1.007511e-01 -0.224364938
## 215 Retail -0.54162222 -0.6955489007 -0.0163762810 1.424171e-01 -0.152658315
## 216 Horeca -1.23239191 -0.2683704471 0.2912940521 -1.525642e-02 0.112285888
## 217 Retail -3.65784251 -1.5024946145 -0.4451166133 3.442908e-01 0.657875917
## 218 Horeca 1.03509689 0.0266087310 0.1292185239 4.633317e-02 -0.017602064
## 219 Retail -1.19058168 0.6205930559 1.2442387713 7.184164e-01 0.142727311
## 220 Horeca 1.25137280 -0.2392367905 -0.0817948446 2.619077e-02 -0.024885647
## 221 Horeca 1.16786662 -0.1694031479 0.1501129365 2.960327e-02 -0.038677735
## 222 Horeca -0.30619270 -0.8089351138 0.0668910915 -1.868201e-01 0.063360480
## 223 Horeca 1.02353682 0.5442296394 -0.7992298261 8.139072e-02 0.023241419
## 224 Retail 0.64173440 0.4433723400 -0.3296613548 1.340806e-01 0.105076655
## 225 Horeca 1.19242546 -0.3378506721 0.2671314257 4.137322e-02 -0.022546599
## 226 Horeca 0.74927539 -0.3702922405 0.2832530799 -9.813612e-02 0.063127379
## 227 Retail -0.04166179 -0.1845337776 0.1953124055 -4.971583e-03 0.146592921
## 228 Horeca 1.03747427 -0.1018997011 0.0652443951 -9.734645e-02 -0.063282394
## 229 Horeca 0.74782120 -0.6691384055 -0.0398167843 3.062108e-01 -0.753030645
## 230 Horeca 0.82806814 0.5910908116 -0.5551384969 -1.856014e-02 -0.089465542
## 231 Retail 0.25762310 1.0470755800 -0.5119581753 -1.145021e-01 0.051283570
## 232 Horeca 0.14712185 -0.2486236341 0.1632538632 -9.088454e-01 -0.116555921
## 233 Horeca 0.92806057 -0.3530682004 0.3031763812 2.615664e-02 0.114450635
## 234 Horeca 0.77748264 -0.4430065220 0.1067856518 -4.316804e-01 0.059574527
## 235 Horeca 0.67882658 0.5685557802 0.1896331714 1.585129e-01 0.034903691
## 236 Horeca 0.58424690 -0.3544175668 0.1247594862 -5.103974e-01 -0.111243449
## 237 Horeca 1.07019195 -0.2560573276 -0.0902724213 6.404733e-02 0.048960534
## 238 Horeca 0.93984852 0.4097679695 -0.1117504327 -2.455267e-01 -0.140479637
## 239 Horeca 1.29676093 -0.3771593082 0.1253457821 -1.504406e-02 -0.080820647
## 240 Horeca 0.65211081 0.6117600861 -0.0475416452 1.822848e-01 -0.037125264
## 241 Horeca 0.35751675 1.5650061126 -0.8886851108 2.372639e-01 0.233027565
## 242 Horeca 0.96409594 -0.0619058462 0.1362730091 2.831163e-02 -0.022388607
## 243 Horeca 1.02852505 0.0209240042 -0.2246841232 1.443754e-01 -0.002387319
## 244 Horeca 0.42242573 -0.0883244925 0.6300559875 1.449717e-01 -0.041947263
## 245 Horeca -0.37409228 -0.2051916783 0.3552773511 -7.683646e-02 0.167212011
## 246 Retail -1.17838892 -0.5677000690 0.3926909992 7.040641e-01 -0.434158944
## 247 Horeca 0.99935781 -0.2027092622 0.1142067686 -1.174565e-01 -0.067239648
## 248 Horeca 1.26979462 -0.1376011824 0.0892026613 5.425859e-02 -0.100974997
## 249 Horeca 0.74868436 -0.3609679907 0.3041702147 -4.226251e-01 -0.047178655
## 250 Horeca 0.81396957 0.3749872762 -0.6333171467 -2.174539e-01 -0.138534187
## 251 Horeca 1.04468274 -0.1831538258 0.1467280904 -7.118688e-02 -0.037489850
## 252 Retail -5.00768849 0.2866944486 -0.4530671996 4.696430e-01 -0.518324418
## 253 Horeca 0.74545878 0.8487520877 -0.5316791722 2.080796e-01 0.131960206
## 254 Horeca -0.38605647 -0.3822564073 0.3596740591 -1.697875e-01 1.053331483
## 255 Horeca -0.70708219 0.9391578638 0.4174818883 -1.347493e+00 -0.181354924
## 256 Horeca 1.18411490 0.0030724566 -0.1056092382 8.228318e-02 -0.039791764
## 257 Horeca 0.63210547 -0.4617583277 0.2382291091 -3.355262e-01 0.201599925
## 258 Horeca 0.60371331 0.1584360306 -0.4021340143 2.429649e-01 -0.537359370
## 259 Horeca 0.51724649 1.0841565656 0.0813394709 3.147487e-02 -0.197104415
## 260 Horeca 0.38236102 -0.0600224883 -0.0825430899 -1.448918e-01 0.252324354
## 261 Horeca 0.77157492 -0.4143575173 0.3222401594 -3.760689e-01 -0.093166151
## 262 Horeca 1.16886889 0.4671003805 -0.6890125078 -7.043557e-03 -0.075260316
## 263 Horeca 1.08603962 -0.3224084602 0.2292812684 -5.347571e-03 -0.065522333
## 264 Horeca 0.50559973 -0.1198310239 -0.4845642221 3.683120e-01 -0.046730481
## 265 Retail -1.05801199 -0.7327306364 0.2015378961 -2.695094e-02 0.128243055
## 266 Horeca -1.65734964 1.7937030127 -0.3176590716 -1.632266e+00 0.531331804
## 267 Retail -1.47739059 -0.1772552412 0.1448843315 2.739655e-01 0.750619450
## 268 Horeca 0.72868453 0.7388604273 0.4633191765 4.314102e-01 -0.139527389
## 269 Retail -1.21350291 -0.8331254104 -0.1733097803 2.719002e-01 0.427226378
## 270 Horeca 1.23813362 -0.2040031259 -0.1028955543 5.837019e-02 -0.082046653
## 271 Horeca 1.19514203 0.2171972169 -0.5560636672 -3.087829e-02 -0.091495871
## 272 Horeca 0.78067858 -0.0285014779 0.4761824614 -3.323474e-01 -0.080771179
## 273 Horeca 0.26602762 -0.2600598349 0.4141737602 -5.980265e-01 0.329535881
## 274 Horeca 0.86878444 0.5324167641 -0.0225250867 -4.330202e-02 -0.111256960
## 275 Horeca 0.97282972 -0.2621784812 0.3694564929 4.112342e-02 -0.114859043
## 276 Horeca 1.22069804 -0.3548028456 0.2178276618 -1.359238e-01 -0.121674632
## 277 Horeca 0.38108645 0.5359681743 0.1031818081 1.588676e-01 0.228136410
## 278 Horeca 1.07846333 1.8653583443 -2.2187714566 1.341660e-01 -0.237361123
## 279 Horeca 0.87750350 0.5586473422 -0.2976317207 3.982789e-02 -0.030181815
## 280 Retail -0.22439955 -0.2780541521 0.2576621230 6.954580e-02 0.028826443
## 281 Horeca 0.92072808 -0.1969571181 0.3540777128 -1.174575e-01 0.008145334
## 282 Retail 0.04172049 -0.0827385077 0.4799604369 -1.985353e-01 -0.063973268
## 283 Horeca 0.56179348 0.5294798027 -0.3505102112 -3.311987e-02 -0.019932544
## 284 Horeca 0.77559110 1.2246245312 -0.9328150131 -7.866405e-02 -0.107268673
## 285 Horeca -0.05666773 1.0332866463 -0.6082059064 3.097958e-01 0.613305200
## 286 Horeca 1.07514112 -0.4990147752 0.0360851368 6.764338e-02 0.101806296
## 287 Horeca 0.99534417 -0.3724699669 -0.0025361652 -1.141551e-01 -0.206668238
## 288 Horeca 0.87483219 0.8238467598 -0.7660903317 6.233610e-02 -0.026198954
## 289 Horeca 1.19971862 -0.4370617387 0.1507336728 2.377307e-02 -0.080498744
## 290 Horeca 1.33657531 -0.3792644504 0.0403934684 -1.991985e-02 -0.078747463
## 291 Horeca 0.83674885 -0.2326950986 0.4778908332 7.063094e-02 -0.094983491
## 292 Horeca 0.85316130 -0.0776399639 0.0255349598 -1.724166e-01 0.065639153
## 293 Horeca 0.69360374 0.1417127149 -0.1231390079 -7.944642e-03 0.043145957
## 294 Retail -0.93965965 -0.6554126047 0.0144458692 -3.368204e-01 -0.092794885
## 295 Horeca 0.59455930 -0.1573054188 0.4481372130 2.453625e-01 0.214344165
## 296 Retail 0.66171399 -0.6451195060 0.1053069563 1.281564e-01 -0.038034651
## 297 Horeca 0.90049568 -0.0190226696 -0.0533317316 1.344791e-01 0.026534235
## 298 Retail 0.25180413 -0.5274174486 -0.0489267035 1.892655e-01 -0.140887343
## 299 Retail -0.16562608 -0.5647513335 0.0893655028 2.460353e-01 -0.051401842
## 300 Horeca 1.15462330 -0.5205877239 0.2356021757 9.127424e-05 0.001409648
## 301 Retail 0.06749116 -0.1726847894 0.4762957660 -8.485776e-02 -0.093726153
## 302 Retail -1.87238584 -0.9062380384 -0.4427004461 -1.810361e-01 0.108661941
## 303 Retail -0.36075328 -0.8370400050 0.0032583493 2.182948e-01 -0.296139923
## 304 Retail -0.89344120 -1.2389830186 -0.3587903929 7.500908e-01 -0.514394929
## 305 Retail -2.24170924 -0.9151722866 0.0047365098 1.077483e+00 -0.014103893
## 306 Retail -0.57018410 -0.5842186912 0.0578018787 -8.680445e-01 -0.071166812
## 307 Retail -1.88935546 -0.5541561209 -0.0993321247 -2.146956e-02 0.333094843
## 308 Horeca 0.92559692 -0.2371239152 0.2679024918 -5.256295e-02 0.020162445
## 309 Horeca 1.05503352 -0.4215247836 0.2968103229 5.963136e-02 0.065581698
## 310 Retail -1.82444685 -0.4800857869 0.0137381216 -1.292307e+00 -0.197719739
## 311 Horeca 0.91380091 1.4544571140 -1.3567395155 1.620224e-01 -0.067659925
## 312 Horeca 0.64646544 -0.2336199078 -0.2728305098 5.699709e-02 0.444370877
## 313 Retail -2.05651935 -1.5961639143 -0.8061189963 1.441392e+00 -1.124041662
## 314 Horeca 1.10515579 0.0942827022 -0.3658363964 4.389359e-02 0.019092121
## 315 Horeca 0.58629339 -0.2366852388 0.1994980699 2.435903e-01 0.306900770
## 316 Retail -1.18632311 0.1134601388 0.8352376886 -6.227835e-01 0.062245747
## 317 Horeca 1.04565960 0.0243938808 0.0831196910 4.934935e-02 0.003501565
## 318 Horeca 0.55882703 -0.1724359049 0.4057778341 8.754597e-02 0.179102456
## 319 Horeca 0.88204365 -0.3180530565 -0.0985570540 -1.318735e-01 0.041084475
## 320 Retail -3.11235419 -0.6616337617 0.0320866751 -1.164397e+00 -0.730470849
## 321 Horeca 0.88439078 -0.3152197306 0.3659850754 -2.408060e-01 -0.013520147
## 322 Horeca 0.80386112 -0.0072506990 0.0513815263 1.045981e-01 0.204073016
## 323 Horeca 0.92745036 -0.1201143087 -0.3393779899 1.744727e-01 -0.088752154
## 324 Horeca 0.37271862 -0.5907448216 0.0313892316 4.454996e-01 0.516413252
## 325 Horeca 0.85971976 0.0136909553 0.1573108564 -1.846572e-01 0.003240288
## 326 Horeca -1.78946833 9.4426161661 -7.3561656089 -1.262653e-01 0.172452266
## 327 Horeca 1.05267151 0.0916580173 -0.0880866187 2.103203e-03 -0.098249788
## 328 Horeca 1.17723864 -0.4219320559 0.2890068608 1.941328e-03 -0.008117440
## 329 Horeca 0.81408444 0.8645867977 -0.5709617552 1.088298e-01 0.029775378
## 330 Horeca 0.85138951 0.2466297340 -0.3962137780 1.314342e-01 0.121544020
## 331 Horeca 0.81990469 0.1028458245 -0.0887119701 1.122326e-01 0.204217975
## 332 Retail -2.55569469 -0.9119772593 -0.2422695809 1.565106e-02 0.445203963
## 333 Horeca 0.81764691 0.3357835077 0.5424978555 -2.891576e-03 -0.118900424
## 334 Retail -7.61379702 -3.4878261273 -1.8570054614 4.487063e+00 -0.492430881
## 335 Retail 0.73733540 1.8203153674 -0.6665945815 4.988941e-01 -0.104095182
## 336 Retail -0.43016311 -0.2108130517 0.3183683323 1.198782e-01 0.026361034
## 337 Horeca 1.12215088 -0.3190418064 0.3242381916 -4.171648e-02 -0.053885459
## 338 Horeca 0.95236916 0.7486749232 -0.7833034255 1.236485e-01 -0.040856249
## 339 Horeca 0.77302224 1.6893212630 -1.9971202384 3.868789e-01 0.331097800
## 340 Horeca 0.67925139 1.1382025886 -0.7816151404 3.759789e-01 0.111049057
## 341 Retail -0.44952190 -0.7286057941 0.1357307410 5.248944e-01 -0.468668348
## 342 Retail -0.49874907 -0.3767392711 0.3492630012 3.240041e-01 -0.081203551
## 343 Horeca -0.03297929 -0.5029489774 0.3096893528 1.177555e-02 -0.379628062
## 344 Retail -2.53250139 -1.5660071985 -0.8480530559 1.184938e+00 -0.359835221
## 345 Horeca 1.13340753 -0.1952182547 -0.0133121117 -1.458200e-02 -0.026484205
## 346 Horeca 0.22596844 -0.7694471361 0.0206476758 2.730768e-01 -0.041278788
## 347 Retail -0.94277386 -0.4648303557 -0.2772970552 3.357660e-01 0.052682251
## 348 Retail -0.52623469 -0.2992166497 -0.1906294560 5.170232e-02 0.090517992
## 349 Horeca 0.89883641 -0.3013837867 0.1566870505 -4.785936e-02 -0.155021430
## 350 Retail -2.40481023 -0.9960767917 -0.5310822389 -4.374715e-02 -0.394974382
## 351 Horeca 1.08068712 -0.1237118941 0.1927739106 6.405186e-02 -0.016769761
## 352 Retail -2.45061408 -0.5584735441 0.0419149034 8.628946e-01 -0.367013462
## 353 Horeca 1.19422964 -0.4293999671 0.1558240037 -5.857045e-02 -0.012704664
## 354 Retail -1.46109306 -1.0443346120 -0.0859166808 7.205129e-01 0.203389284
## 355 Horeca 0.29654054 0.8630742744 -0.1383954212 -3.401633e-01 -0.240078342
## 356 Horeca 1.19246382 -0.5482961618 0.2104436785 -7.319833e-03 0.017614488
## 357 Horeca 1.30670647 -0.0029419227 -0.0920076981 6.454974e-02 -0.118117924
## 358 Retail -0.84837304 -1.2653251323 -0.3054295861 1.059554e+00 0.619631964
## 359 Horeca -0.53430822 1.4509195863 0.4951650461 -1.488780e+00 -0.307004553
## 360 Horeca 0.74548879 -0.3141877231 0.4084485713 -5.018286e-01 -0.030554517
## 361 Horeca 0.95060230 -0.1063642743 -0.0303243494 -1.610490e-01 -0.059279836
## 362 Horeca 1.24298882 -0.3289021623 0.1503307078 8.015338e-03 -0.078577675
## 363 Horeca 1.04927604 -0.3656586146 0.3065814927 -2.120530e-02 0.028795306
## 364 Horeca 0.87486904 -0.6155984555 0.1869141366 1.449102e-01 0.031142672
## 365 Horeca 1.13722957 -0.3566829731 0.1603429922 3.141357e-02 -0.081879125
## 366 Retail -0.34134077 0.0528651642 0.5204387607 2.484323e-01 -0.266636410
## 367 Horeca 1.06478454 -0.3160073629 0.1713890889 -1.369749e-01 -0.037004496
## 368 Horeca 1.23457189 -0.3020715155 0.1031540306 -3.290657e-02 -0.118323974
## 369 Horeca 1.09202865 -0.1860571487 0.0523766298 1.397055e-02 0.035019264
## 370 Horeca 1.29790056 -0.3646317914 0.1456950323 1.026699e-02 -0.070216959
## 371 Retail 0.54728205 0.0660108492 0.5275880023 4.670435e-03 0.109653457
## 372 Horeca 0.92861428 0.7341864175 -0.7960212484 5.201769e-02 -0.132267223
## 373 Horeca 0.55848361 0.6329891063 1.2548922421 1.947481e-01 -0.193946445
## 374 Retail -0.01036762 0.1984867185 0.6528332213 2.705561e-02 0.057534446
## 375 Horeca 1.02837629 -0.2211011595 0.1777392160 -1.044276e-01 -0.058081877
## 376 Horeca 1.15932849 -0.5015726865 0.1543070714 -9.802522e-02 -0.093532531
## 377 Retail -0.77356526 0.1996188872 -0.5105311814 8.662076e-03 0.146226030
## 378 Horeca 0.88358086 -0.1532556029 0.3813297561 -1.293612e-01 0.029117565
## 379 Horeca 0.93923945 -0.2746083703 0.4739350118 -1.933370e-01 -0.016908645
## 380 Retail 0.27600519 -0.6575609068 0.1558497541 -1.804023e-01 0.539501791
## 381 Horeca 1.07810889 -0.0128717819 -0.3024832323 5.457804e-02 -0.056683715
## 382 Horeca 0.81131596 1.0058196043 -1.0577260590 -3.067384e-01 -0.107566207
## 383 Horeca -0.12863861 0.3117748537 0.4582050708 -9.939952e-02 0.162220332
## 384 Horeca 0.98212572 0.0222401601 -0.3036920467 4.719205e-02 0.066127080
## 385 Horeca -1.64808006 1.1586559064 0.9605663032 -1.324026e+00 0.742990749
## 386 Horeca 1.10233193 0.0088755009 0.0972514015 8.876743e-02 -0.053949151
## 387 Horeca 0.82259230 -0.0935972530 0.1765052575 -1.786855e-01 0.008277633
## 388 Horeca 1.04129188 -0.0912372095 0.1742296693 -3.926493e-02 -0.062097721
## 389 Horeca 1.19768522 -0.2641713568 0.0789849464 -1.220946e-03 -0.064952858
## 390 Horeca 1.09437876 -0.0030619385 -0.0478148524 -2.252481e-02 -0.068766279
## 391 Horeca 1.06891237 0.4179833336 -0.3424848203 7.987405e-02 -0.108186282
## 392 Horeca 0.88438236 -0.0417631467 0.5367800244 -3.089990e-02 -0.009649391
## 393 Horeca 0.79981986 -0.3397531358 0.2968846699 -2.819700e-01 0.110441519
## 394 Horeca 0.48759544 0.8695421826 -0.8090023384 -4.435117e-01 0.028695796
## 395 Horeca 1.07628493 -0.3243979663 0.1054144579 6.200560e-02 0.097367055
## 396 Horeca 1.08292394 -0.1408151659 -0.1508761886 -5.685268e-03 -0.156053509
## 397 Retail -0.65441107 0.1365619541 0.2609186633 -5.374683e-01 -0.017928094
## 398 Horeca 1.06672699 0.5739678319 -0.5833083159 -5.032264e-03 -0.068046024
## 399 Horeca 1.21812567 0.2573167088 -0.4850298560 -3.179681e-02 -0.108576616
## 400 Horeca 1.20418087 -0.2977446541 0.0719496515 3.635687e-02 -0.118696408
## 401 Horeca 1.12755720 0.1486469749 -0.0539299714 7.907698e-02 -0.080788486
## 402 Horeca 0.78619937 1.7607701632 -1.2401567867 8.773626e-02 -0.092231125
## 403 Horeca 0.70963764 -0.4824173163 0.2787551961 -3.455904e-01 0.247948235
## 404 Horeca 0.21181784 -0.4378501159 0.3382349083 -1.023084e+00 0.087221718
## 405 Horeca 0.65039342 0.1682494910 -0.2479710243 -2.358100e-01 -0.038949793
## 406 Horeca 1.13695208 -0.2329491833 0.0020048404 5.289853e-03 -0.124123853
## 407 Horeca 0.43799628 0.9861577681 -1.0141918729 -1.341328e-01 0.017341293
## 408 Retail -1.67259278 -0.5997607604 -0.4539003847 -1.927750e-01 0.088799367
## 409 Retail 0.36550163 -0.4654167058 -0.0653570248 4.368427e-03 -0.044121872
## 410 Horeca 0.05904374 0.7407264885 0.9812353376 5.321543e-01 -0.116912163
## 411 Horeca 0.58114647 -0.1053616044 0.3728519656 2.555079e-01 -0.091531240
## 412 Horeca 0.54871526 0.5993113197 1.0280690648 2.474061e-01 -0.033336374
## 413 Horeca 0.02754893 -0.8683954018 0.0009452655 2.004207e-01 0.396172149
## 414 Horeca 0.18022987 2.4627986053 -1.8610262286 1.696222e-01 0.081699407
## 415 Horeca 0.84472130 0.2166544351 -0.5858918678 3.730761e-02 -0.052819470
## 416 Retail -0.15011103 -0.1654789686 0.2521128931 6.515206e-02 -0.052293459
## 417 Retail -0.94319868 -0.6282524920 0.0694434201 -2.856556e-01 -0.328750555
## 418 Horeca -0.17681577 -0.5846549679 0.2174968459 9.846607e-02 0.179411157
## 419 Retail -1.21247875 -0.9451190928 -0.0111536007 2.085788e-01 0.281727286
## 420 Horeca 0.67045226 -0.2169645295 0.4594481571 -7.930226e-02 -0.225166310
## 421 Horeca -0.70505273 -0.7893865579 0.1792825081 4.685864e-01 -0.138527213
## 422 Retail -0.06490484 -0.3007384881 0.3109499418 1.898877e-01 0.016876618
## 423 Horeca 0.82591686 -0.2892677213 0.3292781858 1.754135e-01 0.035366768
## 424 Retail 0.57180936 -0.3995984651 0.1544486982 -6.623976e-02 -0.049472294
## 425 Retail 0.04046836 -0.7367264203 -0.0847164943 3.219454e-01 0.343336774
## 426 Horeca 0.76883248 2.0500342258 -1.5657601158 1.670196e-01 -0.067827419
## 427 Horeca -0.93848842 -0.0821362098 -0.0534415939 1.076078e-02 0.138959378
## 428 Horeca -0.43132555 2.0067711242 -1.5734003459 -1.398859e+00 0.039329073
## 429 Horeca 0.51934102 -0.2273851246 -0.0315692426 -4.106207e-01 0.096672075
## 430 Horeca 0.83217183 -0.0517546591 0.7913966759 1.911758e-01 0.080207639
## 431 Horeca -0.12732308 -0.2510251070 0.4661498794 3.030175e-01 1.035711609
## 432 Horeca 0.28430937 1.6278170123 -1.4322862099 -6.732602e-02 -0.051096480
## 433 Horeca 0.83664364 -0.5884685158 0.1925679473 1.462679e-01 0.052584928
## 434 Horeca 0.89763536 -0.0286593561 0.3618008079 -1.269600e-01 -0.105069502
## 435 Horeca 0.27267232 -0.4987640539 0.1838051451 7.266804e-02 0.119401988
## 436 Horeca -0.78171970 1.7262064236 -1.2339946527 -4.534560e-01 0.892440952
## 437 Horeca 1.00383404 0.6000966110 0.1372499975 1.617472e-01 -0.153667550
## 438 Retail -3.47543102 -1.2015869428 -0.1938524404 5.134742e-01 -0.065875377
## 439 Horeca 0.91187529 0.0286815529 0.5761825595 9.421507e-02 -0.030771798
## 440 Horeca 1.06427400 -0.6008476585 0.2126003922 -8.899895e-02 0.011009682
# Means of scores for all the PC's classified by Channel status
tabmeansPC <- aggregate(wholesale_channel_pca[,2:6],by=list(Channel=wholesale$Channel),mean)
tabmeansPC
## Channel PC1 PC2 PC3 PC4 PC5
## 1 Horeca 0.6635514 0.2217411 -0.01580142 -0.02354574 0.008518129
## 2 Retail -1.3925234 -0.4653440 0.03316073 0.04941289 -0.017876074
tabmeansPC <- tabmeansPC[rev(order(tabmeansPC$Channel)),]
tabmeansPC
## Channel PC1 PC2 PC3 PC4 PC5
## 2 Retail -1.3925234 -0.4653440 0.03316073 0.04941289 -0.017876074
## 1 Horeca 0.6635514 0.2217411 -0.01580142 -0.02354574 0.008518129
tabfmeans <- t(tabmeansPC[,-1])
tabfmeans
## 2 1
## PC1 -1.39252342 0.663551430
## PC2 -0.46534399 0.221741094
## PC3 0.03316073 -0.015801420
## PC4 0.04941289 -0.023545742
## PC5 -0.01787607 0.008518129
colnames(tabfmeans) <- t(as.vector(tabmeansPC[1]$Channel))
tabfmeans
## Retail Horeca
## PC1 -1.39252342 0.663551430
## PC2 -0.46534399 0.221741094
## PC3 0.03316073 -0.015801420
## PC4 0.04941289 -0.023545742
## PC5 -0.01787607 0.008518129
# Standard deviations of scores for all the PC's classified by Channel status
tabsdsPC <- aggregate(wholesale_channel_pca[,2:6],by=list(Channel=wholesale$Channel),sd)
tabfsds <- t(tabsdsPC[,-1])
colnames(tabfsds) <- t(as.vector(tabsdsPC[1]$Channel))
tabfsds
## Horeca Retail
## PC1 0.7538240 2.0362088
## PC2 1.3036314 0.7419858
## PC3 0.8382756 0.5604593
## PC4 0.3619094 0.7835259
## PC5 0.1906575 0.3495700
t.test(PC1~wholesale$Channel,data=wholesale_channel_pca)
##
## Welch Two Sample t-test
##
## data: PC1 by wholesale$Channel
## t = 11.658, df = 159.69, p-value < 2.2e-16
## alternative hypothesis: true difference in means between group Horeca and group Retail is not equal to 0
## 95 percent confidence interval:
## 1.707764 2.404386
## sample estimates:
## mean in group Horeca mean in group Retail
## 0.6635514 -1.3925234
t.test(PC2~wholesale$Channel,data=wholesale_channel_pca)
##
## Welch Two Sample t-test
##
## data: PC2 by wholesale$Channel
## t = 7.0199, df = 424.67, p-value = 8.846e-12
## alternative hypothesis: true difference in means between group Horeca and group Retail is not equal to 0
## 95 percent confidence interval:
## 0.4947011 0.8794690
## sample estimates:
## mean in group Horeca mean in group Retail
## 0.2217411 -0.4653440
t.test(PC3~wholesale$Channel,data=wholesale_channel_pca)
##
## Welch Two Sample t-test
##
## data: PC3 by wholesale$Channel
## t = -0.72426, df = 390.94, p-value = 0.4693
## alternative hypothesis: true difference in means between group Horeca and group Retail is not equal to 0
## 95 percent confidence interval:
## -0.18187283 0.08394853
## sample estimates:
## mean in group Horeca mean in group Retail
## -0.01580142 0.03316073
t.test(PC4~wholesale$Channel,data=wholesale_channel_pca)
##
## Welch Two Sample t-test
##
## data: PC4 by wholesale$Channel
## t = -1.0572, df = 170.29, p-value = 0.2919
## alternative hypothesis: true difference in means between group Horeca and group Retail is not equal to 0
## 95 percent confidence interval:
## -0.20919064 0.06327337
## sample estimates:
## mean in group Horeca mean in group Retail
## -0.02354574 0.04941289
t.test(PC5~wholesale$Channel,data=wholesale_channel_pca)
##
## Welch Two Sample t-test
##
## data: PC5 by wholesale$Channel
## t = 0.84204, df = 182.07, p-value = 0.4009
## alternative hypothesis: true difference in means between group Horeca and group Retail is not equal to 0
## 95 percent confidence interval:
## -0.0354529 0.0882413
## sample estimates:
## mean in group Horeca mean in group Retail
## 0.008518129 -0.017876074
## F ratio tests
var.test(PC1~wholesale$Channel,data=wholesale_channel_pca)
##
## F test to compare two variances
##
## data: PC1 by wholesale$Channel
## F = 0.13706, num df = 297, denom df = 141, p-value < 2.2e-16
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.1023803 0.1808180
## sample estimates:
## ratio of variances
## 0.1370551
var.test(PC2~wholesale$Channel,data=wholesale_channel_pca)
##
## F test to compare two variances
##
## data: PC2 by wholesale$Channel
## F = 3.0869, num df = 297, denom df = 141, p-value = 8.931e-13
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 2.305895 4.072535
## sample estimates:
## ratio of variances
## 3.086871
var.test(PC3~wholesale$Channel,data=wholesale_channel_pca)
##
## F test to compare two variances
##
## data: PC3 by wholesale$Channel
## F = 2.2371, num df = 297, denom df = 141, p-value = 1.637e-07
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 1.671116 2.951425
## sample estimates:
## ratio of variances
## 2.2371
var.test(PC4~wholesale$Channel,data=wholesale_channel_pca)
##
## F test to compare two variances
##
## data: PC4 by wholesale$Channel
## F = 0.21335, num df = 297, denom df = 141, p-value < 2.2e-16
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.1593728 0.2814747
## sample estimates:
## ratio of variances
## 0.2133502
var.test(PC5~wholesale$Channel,data=wholesale_channel_pca)
##
## F test to compare two variances
##
## data: PC5 by wholesale$Channel
## F = 0.29747, num df = 297, denom df = 141, p-value < 2.2e-16
## alternative hypothesis: true ratio of variances is not equal to 1
## 95 percent confidence interval:
## 0.2222084 0.3924513
## sample estimates:
## ratio of variances
## 0.2974675
# Levene's tests (one-sided)
library(car)
(LTPC1 <- leveneTest(PC1~wholesale$Channel,data=wholesale_channel_pca))
## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 1 52.142 2.3e-12 ***
## 438
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(p_PC1_1sided <- LTPC1[[3]][1]/2)
## [1] 1.150248e-12
(LTPC2 <- leveneTest(PC2~wholesale$Channel,data=wholesale_channel_pca))
## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 1 1.0541 0.3051
## 438
(p_PC2_1sided=LTPC2[[3]][1]/2)
## [1] 0.152567
(LTPC3 <- leveneTest(PC3~wholesale$Channel,data=wholesale_channel_pca))
## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 1 0.5024 0.4788
## 438
(p_PC3_1sided <- LTPC3[[3]][1]/2)
## [1] 0.2394059
(LTPC4 <- leveneTest(PC4~wholesale$Channel,data=wholesale_channel_pca))
## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 1 20.69 7.001e-06 ***
## 438
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(p_PC4_1sided <- LTPC4[[3]][1]/2)
## [1] 3.500348e-06
(LTPC5 <- leveneTest(PC5~wholesale$Channel,data=wholesale_channel_pca))
## Warning in leveneTest.default(y = y, group = group, ...): group coerced to
## factor.
## Levene's Test for Homogeneity of Variance (center = median)
## Df F value Pr(>F)
## group 1 34.481 8.517e-09 ***
## 438
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(p_PC5_1sided <- LTPC5[[3]][1]/2)
## [1] 4.258356e-09
# Plotting the scores for the first and second components
plot(wholesale_channel_pca$PC1, wholesale_channel_pca$PC2,pch=ifelse(wholesale_pca$Channel == "Retail",1,16),xlab="PC1", ylab="PC2", main="Wholesale Customers against PC1&PC2")
abline(h=0)
abline(v=0)
legend("bottomleft", legend=c("Retail","Horesca"), pch=c(1,16))
plot(eigen_wholesale, xlab = "Component number", ylab = "Component variance", type = "l", main = "Scree diagram")
plot(log(eigen_wholesale), xlab = "Component number",ylab = "log(Component variance)", type="l",main = "Log(eigenvalue) diagram")
print(summary(wholesale_pca))
## Importance of components:
## PC1 PC2 PC3 PC4 PC5
## Standard deviation 1.6255 1.1958 0.7595 0.53568 0.2530
## Proportion of Variance 0.5284 0.2860 0.1154 0.05739 0.0128
## Cumulative Proportion 0.5284 0.8145 0.9298 0.98720 1.0000
diag(cov(wholesale_pca$x))
## PC1 PC2 PC3 PC4 PC5
## 2.64223659 1.42999181 0.57682096 0.28695719 0.06399345
xlim <- range(wholesale_pca$x[,1])
wholesale_pca$x[,1]
## [1] -0.19707283 -0.45313294 -0.81180172 0.79342916 -0.11570147
## [6] 0.14370629 0.32567049 -0.15665440 0.48890741 -1.62027497
## [11] -0.66758413 0.92597350 -0.92658585 -0.82672223 -0.80858534
## [16] 0.93709140 -0.60479469 0.33914993 -0.29126066 0.29954840
## [21] 0.33682556 1.09654804 0.26619036 -4.58054505 -1.19755447
## [26] 0.15537156 1.03266607 1.09811094 -3.14687957 0.88052223
## [31] -0.05215116 0.69579690 0.98632753 0.41807632 1.02591988
## [36] -0.21643153 0.24158323 -0.97020398 -1.62332525 0.95272626
## [41] 0.08308879 0.25869103 -0.87588116 -2.00255094 -0.30164586
## [46] -2.83141245 -1.90336183 -9.41725404 -0.44041724 -3.63590895
## [51] 0.91517116 0.47041131 0.34153413 -0.75096260 1.02036283
## [56] 0.48573185 -4.63920836 -0.95925425 1.08902399 0.02055344
## [61] 0.20266611 -8.37149191 -0.04643766 -1.44256223 0.84129649
## [66] -5.88216805 0.42975520 -0.59711484 0.22115034 1.02170230
## [71] 0.84070633 -1.73915275 0.62067938 0.26682334 -0.04638691
## [76] 1.20012549 0.54017219 -2.77004981 1.12399443 0.65209963
## [81] 1.03868601 -1.10479248 -0.56696336 1.03054389 0.39812160
## [86] -12.68123458 -8.39266413 -0.92068706 1.01342557 0.44301966
## [91] 1.19321062 0.80614475 -5.24057761 0.52578694 -0.79761716
## [96] 0.71560919 0.24404605 1.32938626 1.32246301 1.02727861
## [101] -1.13082005 -1.34423210 -0.21246138 0.06820127 0.80468449
## [106] 0.94469735 -0.66901612 -1.47652662 -0.04077613 -1.70666698
## [111] 0.99983015 -1.37687414 0.68923179 0.90109151 1.05901888
## [116] 1.05586310 0.94497402 0.63888952 0.94868598 0.98250864
## [121] 0.96940760 1.00153477 1.28120984 -0.18913115 0.86596557
## [126] 0.40917867 1.01779186 -0.30277111 0.39288434 1.02620109
## [131] 1.00675513 1.30343896 0.95838681 1.18401500 1.07458712
## [136] 1.08937421 -0.11183011 0.20888553 0.47286002 0.67212442
## [141] 0.28796809 -0.02250288 0.34418432 1.07654549 0.93281684
## [146] -3.18443785 1.06717252 0.80824332 1.22430136 1.05447741
## [151] 1.04333128 0.84943798 1.02940017 0.39707127 1.38885601
## [156] -2.10534411 -0.94690511 0.99393880 -0.28531006 -1.03017136
## [161] -0.35485260 1.14689210 0.92036981 -3.05168162 -0.14994267
## [166] -1.80878413 -0.54851470 0.71052625 1.24301618 1.12716773
## [171] -0.90926104 -3.27135965 0.20685284 -1.58573375 0.83240063
## [176] -0.53378209 0.23300367 0.34523774 0.52247477 0.63766473
## [181] 0.01290303 -3.32956183 -0.68822721 -7.47744667 1.00703448
## [186] 0.81312626 1.11229463 -0.24041783 -0.72607631 -0.78285913
## [191] 0.74272114 1.27769586 1.09693599 -0.81285702 1.00169591
## [196] 0.45245343 0.08628883 -0.39085008 0.66997842 1.02565202
## [201] -2.23900996 -2.99546346 -0.68180673 1.10109815 0.89280368
## [206] -2.04834810 1.22289397 0.02999763 0.29338844 -2.07821189
## [211] 0.95666185 -5.65091274 1.01303835 -0.07733767 -0.54162222
## [216] -1.23239191 -3.65784251 1.03509689 -1.19058168 1.25137280
## [221] 1.16786662 -0.30619270 1.02353682 0.64173440 1.19242546
## [226] 0.74927539 -0.04166179 1.03747427 0.74782120 0.82806814
## [231] 0.25762310 0.14712185 0.92806057 0.77748264 0.67882658
## [236] 0.58424690 1.07019195 0.93984852 1.29676093 0.65211081
## [241] 0.35751675 0.96409594 1.02852505 0.42242573 -0.37409228
## [246] -1.17838892 0.99935781 1.26979462 0.74868436 0.81396957
## [251] 1.04468274 -5.00768849 0.74545878 -0.38605647 -0.70708219
## [256] 1.18411490 0.63210547 0.60371331 0.51724649 0.38236102
## [261] 0.77157492 1.16886889 1.08603962 0.50559973 -1.05801199
## [266] -1.65734964 -1.47739059 0.72868453 -1.21350291 1.23813362
## [271] 1.19514203 0.78067858 0.26602762 0.86878444 0.97282972
## [276] 1.22069804 0.38108645 1.07846333 0.87750350 -0.22439955
## [281] 0.92072808 0.04172049 0.56179348 0.77559110 -0.05666773
## [286] 1.07514112 0.99534417 0.87483219 1.19971862 1.33657531
## [291] 0.83674885 0.85316130 0.69360374 -0.93965965 0.59455930
## [296] 0.66171399 0.90049568 0.25180413 -0.16562608 1.15462330
## [301] 0.06749116 -1.87238584 -0.36075328 -0.89344120 -2.24170924
## [306] -0.57018410 -1.88935546 0.92559692 1.05503352 -1.82444685
## [311] 0.91380091 0.64646544 -2.05651935 1.10515579 0.58629339
## [316] -1.18632311 1.04565960 0.55882703 0.88204365 -3.11235419
## [321] 0.88439078 0.80386112 0.92745036 0.37271862 0.85971976
## [326] -1.78946833 1.05267151 1.17723864 0.81408444 0.85138951
## [331] 0.81990469 -2.55569469 0.81764691 -7.61379702 0.73733540
## [336] -0.43016311 1.12215088 0.95236916 0.77302224 0.67925139
## [341] -0.44952190 -0.49874907 -0.03297929 -2.53250139 1.13340753
## [346] 0.22596844 -0.94277386 -0.52623469 0.89883641 -2.40481023
## [351] 1.08068712 -2.45061408 1.19422964 -1.46109306 0.29654054
## [356] 1.19246382 1.30670647 -0.84837304 -0.53430822 0.74548879
## [361] 0.95060230 1.24298882 1.04927604 0.87486904 1.13722957
## [366] -0.34134077 1.06478454 1.23457189 1.09202865 1.29790056
## [371] 0.54728205 0.92861428 0.55848361 -0.01036762 1.02837629
## [376] 1.15932849 -0.77356526 0.88358086 0.93923945 0.27600519
## [381] 1.07810889 0.81131596 -0.12863861 0.98212572 -1.64808006
## [386] 1.10233193 0.82259230 1.04129188 1.19768522 1.09437876
## [391] 1.06891237 0.88438236 0.79981986 0.48759544 1.07628493
## [396] 1.08292394 -0.65441107 1.06672699 1.21812567 1.20418087
## [401] 1.12755720 0.78619937 0.70963764 0.21181784 0.65039342
## [406] 1.13695208 0.43799628 -1.67259278 0.36550163 0.05904374
## [411] 0.58114647 0.54871526 0.02754893 0.18022987 0.84472130
## [416] -0.15011103 -0.94319868 -0.17681577 -1.21247875 0.67045226
## [421] -0.70505273 -0.06490484 0.82591686 0.57180936 0.04046836
## [426] 0.76883248 -0.93848842 -0.43132555 0.51934102 0.83217183
## [431] -0.12732308 0.28430937 0.83664364 0.89763536 0.27267232
## [436] -0.78171970 1.00383404 -3.47543102 0.91187529 1.06427400
wholesale_pca$x
## PC1 PC2 PC3 PC4 PC5
## [1,] -0.19707283 -0.3770084356 0.4339928374 -5.086349e-01 -0.001854585
## [2,] -0.45313294 -0.1211597823 0.2609418663 -3.508749e-01 0.040946165
## [3,] -0.81180172 1.3273282020 1.5940953009 4.144155e-01 -0.301861199
## [4,] 0.79342916 0.6658443374 -0.3359082992 2.853570e-01 0.057266232
## [5,] -0.11570147 1.0073354473 0.7846578714 3.653701e-01 -0.003812347
## [6,] 0.14370629 -0.2180994333 0.4452745197 -4.774821e-01 -0.059000770
## [7,] 0.32567049 -0.6325704892 0.1196417115 1.399425e-01 -0.054904769
## [8,] -0.15665440 -0.0331363080 0.4012580200 2.786108e-01 0.032831032
## [9,] 0.48890741 -0.4938233270 0.2485820432 -1.502553e-02 0.081354092
## [10,] -1.62027497 -0.5048683883 0.1499964109 1.363545e-01 0.145687282
## [11,] -0.66758413 -0.0238881161 -0.3383420998 4.676957e-01 -0.071596678
## [12,] 0.92597350 -0.3515756476 0.0822191593 1.100768e-01 0.137720104
## [13,] -0.92658585 -0.1074909163 0.7247966859 -4.006276e-01 0.084630659
## [14,] -0.82672223 -0.5293360636 -0.4619419906 3.523687e-01 0.011172418
## [15,] -0.80858534 -0.3934991730 0.4585439002 -7.316764e-02 -0.020590692
## [16,] 0.93709140 -0.5308636604 0.2043574976 9.831297e-02 0.032723673
## [17,] -0.60479469 -0.6384278916 0.2404058097 -1.647392e-01 0.095547612
## [18,] 0.33914993 0.5663431002 1.1904730227 -6.896284e-02 -0.095319576
## [19,] -0.29126066 0.2233895662 0.4970352941 1.829471e-01 0.135411974
## [20,] 0.29954840 -0.6312712075 0.0644977021 2.521058e-01 0.228237979
## [21,] 0.33682556 -0.0861339420 0.4875413015 3.768933e-02 -0.164582644
## [22,] 1.09654804 -0.0043401285 -0.1497704508 7.141227e-02 -0.040058284
## [23,] 0.26619036 1.5683970175 -0.2467060883 6.670989e-01 -0.283900004
## [24,] -4.58054505 3.8072871727 3.3396697767 -1.130469e+00 0.254755186
## [25,] -1.19755447 0.8003953225 0.9263685687 3.438610e-01 0.074691495
## [26,] 0.15537156 -0.8250948908 0.0157524281 4.829123e-02 -0.122135167
## [27,] 1.03266607 0.0159926101 -0.0590410608 1.074156e-01 0.037212525
## [28,] 1.09811094 -0.4373483299 0.2574858397 5.881782e-02 0.095718884
## [29,] -3.14687957 0.1506165427 0.8514050232 -2.440491e-01 0.374539040
## [30,] 0.88052223 -0.2960335906 0.2061557803 1.353125e-02 -0.101725549
## [31,] -0.05215116 -0.0007608697 0.5787210362 4.390835e-01 0.330576240
## [32,] 0.69579690 -0.0888786625 0.1462865658 -2.131695e-01 -0.043052084
## [33,] 0.98632753 -0.5302711469 0.2387360039 3.962267e-02 -0.032243165
## [34,] 0.41807632 0.4822328908 -0.4532962679 -1.084847e-01 0.315119579
## [35,] 1.02591988 -0.4642031406 0.2470086458 -8.541622e-02 -0.021926123
## [36,] -0.21643153 -0.7002955975 -0.0286492746 8.763578e-02 0.089179114
## [37,] 0.24158323 0.6313110592 1.0201656795 2.740459e-01 0.025899292
## [38,] -0.97020398 -0.5543555171 -0.1693693299 -2.287695e-01 -0.173107471
## [39,] -1.62332525 -0.9046825507 0.0284863528 -6.876237e-01 0.072911071
## [40,] 0.95272626 1.4991601790 -0.5480032712 3.916575e-01 -0.200711189
## [41,] 0.08308879 2.0275377344 0.1721111919 4.933808e-01 -0.142283907
## [42,] 0.25869103 0.1421617102 0.4567992931 3.539627e-01 -0.122343929
## [43,] -0.87588116 -1.0635936007 -0.1589398770 1.228399e-01 0.005470463
## [44,] -2.00255094 -1.2141592087 -0.4235084566 2.189990e-01 0.292958699
## [45,] -0.30164586 -0.8128614625 -0.0610496539 -1.224052e-01 -0.009380470
## [46,] -2.83141245 0.3536181366 0.8431308911 -6.720454e-01 0.210311577
## [47,] -1.90336183 -0.5432914831 -0.0554886874 -2.103213e-01 0.468640242
## [48,] -9.41725404 0.5414621846 -0.4271519661 -1.731283e+00 0.133925231
## [49,] -0.44041724 -0.5408300715 0.2274220164 1.858785e-01 -0.085748415
## [50,] -3.63590895 -0.9762339518 -0.4172346295 -3.493400e-01 -0.008648759
## [51,] 0.91517116 0.4104644981 0.1479309633 2.485985e-01 -0.124280227
## [52,] 0.47041131 -0.6176023581 0.1716656472 -9.969138e-02 0.179345625
## [53,] 0.34153413 -0.4009520531 0.3295290114 6.842046e-02 -0.084407972
## [54,] -0.75096260 -0.7685290601 -0.0652044882 -3.819017e-01 -0.096389717
## [55,] 1.02036283 0.0487333009 0.1823242891 7.034276e-02 -0.039970438
## [56,] 0.48573185 -0.3152336743 0.2495333559 1.398177e-02 -0.067490936
## [57,] -4.63920836 -0.8901055110 -0.5298270393 -1.038605e+00 -0.819611828
## [58,] -0.95925425 -0.7378871248 0.2151100896 -1.012359e-01 -0.479576833
## [59,] 1.08902399 -0.4058042205 0.2500262845 -1.164280e-01 -0.034073572
## [60,] 0.02055344 -0.4281666899 0.4332603258 4.625049e-02 -0.005978029
## [61,] 0.20266611 -0.8307229912 0.0488423661 2.140045e-01 -0.112791726
## [62,] -8.37149191 -1.5623789638 -1.1584129243 -1.933842e-01 0.319907948
## [63,] -0.04643766 -0.0064623816 -0.3126388497 -6.399385e-02 -0.270890553
## [64,] -1.44256223 -0.3881746020 -0.2539083496 -7.828486e-02 -0.117075631
## [65,] 0.84129649 0.1089106750 -0.1116094122 2.036070e-01 -0.090476223
## [66,] -5.88216805 -2.0643796924 -0.7569200156 1.028312e+00 -0.240375986
## [67,] 0.42975520 -0.8439903706 0.0033292780 3.019871e-01 -0.042364665
## [68,] -0.59711484 -0.6209401671 -0.0494590712 1.373610e-01 0.119889933
## [69,] 0.22115034 0.9618614565 0.1144127302 -2.362520e-01 -0.069370103
## [70,] 1.02170230 -0.4498752241 0.1528820924 -2.238458e-01 -0.120372633
## [71,] 0.84070633 1.2369213016 -1.0142299556 1.233516e-01 0.019609630
## [72,] -1.73915275 2.8610779436 2.4170622052 2.526060e+00 0.464898413
## [73,] 0.62067938 0.7050255622 -1.0362899361 -3.073257e-01 -0.169665352
## [74,] 0.26682334 0.6376948170 -0.8755662868 -1.254282e-01 0.361266482
## [75,] -0.04638691 -0.1674522707 0.3416721379 -5.974311e-02 0.280263771
## [76,] 1.20012549 0.2925598478 -0.1589521213 5.912953e-03 -0.158188044
## [77,] 0.54017219 0.6274661824 -0.7126274387 3.926234e-03 0.235234832
## [78,] -2.77004981 -1.1857563171 -0.3572508458 4.752266e-01 0.244348076
## [79,] 1.12399443 -0.2721741808 -0.0502825534 -2.452565e-02 -0.008690418
## [80,] 0.65209963 -0.1635736239 0.4455307307 1.627898e-02 -0.063766052
## [81,] 1.03868601 -0.4709420234 0.2485400502 9.200612e-02 0.019753232
## [82,] -1.10479248 -1.0377605203 -0.1519433582 -3.801156e-02 -0.183875803
## [83,] -0.56696336 -0.1897705085 0.5070899455 -1.672162e-01 0.108922971
## [84,] 1.03054389 -0.1083993421 0.0575018685 1.189421e-02 -0.086393476
## [85,] 0.39812160 -0.6286896384 -0.0790878932 6.345882e-02 -0.312116534
## [86,] -12.68123458 -2.9055675082 -1.5301790149 1.109718e+00 0.766109027
## [87,] -8.39266413 -0.7648749958 -0.0254756094 -5.643262e+00 -0.986574914
## [88,] -0.92068706 3.3879831694 2.5748630597 1.493591e+00 -0.172326436
## [89,] 1.01342557 0.7716998749 -1.2224864249 1.620546e-01 0.127114509
## [90,] 0.44301966 0.5731766717 0.4416464506 1.520250e-01 0.111153688
## [91,] 1.19321062 -0.0368736054 -0.1796662555 4.390303e-02 -0.016938275
## [92,] 0.80614475 0.8926142932 -0.7902658775 9.552051e-03 -0.091570032
## [93,] -5.24057761 -0.1447202035 0.1233521218 -7.733263e-02 -0.687874557
## [94,] 0.52578694 5.0971997130 -4.2280974876 3.562690e-01 -0.235963847
## [95,] -0.79761716 -0.7786843800 0.0650273452 -6.281708e-01 -0.038072173
## [96,] 0.71560919 -0.4279470962 0.2866668376 -4.319073e-02 0.305115990
## [97,] 0.24404605 -0.8238016100 0.0398452920 2.543221e-01 -0.058548989
## [98,] 1.32938626 -0.4629908981 0.1364874089 -1.157487e-02 -0.068943918
## [99,] 1.32246301 -0.4351711891 0.1309323486 1.898908e-02 -0.058179488
## [100,] 1.02727861 0.2983698332 -0.5129768013 -9.591612e-02 -0.037799311
## [101,] -1.13082005 0.0296427973 0.0885664798 4.577611e-01 -0.473247863
## [102,] -1.34423210 -0.4240373165 0.0836781087 1.010917e-02 0.047409545
## [103,] -0.21246138 -0.1865573632 -0.0137137578 1.731627e-02 -0.260442905
## [104,] 0.06820127 2.4096180816 -1.9396808134 4.447883e-01 0.178855067
## [105,] 0.80468449 -0.3727619490 0.0956486645 3.469641e-02 -0.086245320
## [106,] 0.94469735 -0.1982170834 0.3856879072 1.704796e-01 0.133073495
## [107,] -0.66901612 -0.6188300049 0.3127463650 3.184159e-01 -0.351635129
## [108,] -1.47652662 -0.4917273047 -0.2096213973 1.042837e-01 -0.366056895
## [109,] -0.04077613 -0.3953887590 0.4044253759 -4.101700e-01 -0.011842382
## [110,] -1.70666698 -0.7445501815 -0.0743597119 -8.805089e-01 1.888181050
## [111,] 0.99983015 0.1048203863 0.2865328374 7.158538e-02 -0.063314112
## [112,] -1.37687414 -0.6081606384 0.1224336064 -4.770345e-02 0.202325530
## [113,] 0.68923179 1.2798147189 -0.4339000015 1.794542e-01 -0.120975838
## [114,] 0.90109151 0.2079202525 0.1193587893 2.975898e-02 -0.126406650
## [115,] 1.05901888 0.0493188652 0.1474579566 1.006991e-01 -0.020229691
## [116,] 1.05586310 -0.1034380740 -0.0528084643 1.030625e-01 0.051592527
## [117,] 0.94497402 -0.3443957553 0.0458862013 -1.318167e-01 0.081944110
## [118,] 0.63888952 -0.1290378910 0.2358638727 -1.088179e-01 0.200165919
## [119,] 0.94868598 0.3684258484 -0.3442094906 3.215203e-02 -0.045101450
## [120,] 0.98250864 0.1114467083 -0.1886718345 -8.411286e-02 -0.027206760
## [121,] 0.96940760 -0.0240916571 0.1173633154 1.211556e-01 0.083059013
## [122,] 1.00153477 -0.1658860503 -0.0390138016 -2.630435e-01 -0.062843175
## [123,] 1.28120984 -0.1024026325 0.1511531050 8.324730e-02 -0.121160465
## [124,] -0.18913115 -0.3203897860 -0.1106006465 -7.592123e-01 0.209858651
## [125,] 0.86596557 0.4226150095 -0.1163835099 1.589650e-01 -0.026966052
## [126,] 0.40917867 1.9108688107 -2.0407836107 1.442061e-01 0.194309814
## [127,] 1.01779186 0.6950263922 -0.8546792729 -1.292082e-02 -0.092424266
## [128,] -0.30277111 -0.0382865069 0.6076499875 1.001440e-02 0.248558255
## [129,] 0.39288434 -0.5444758971 0.2361887980 -8.086403e-01 -0.013436955
## [130,] 1.02620109 0.0404906424 0.3923445875 1.777608e-01 -0.109445886
## [131,] 1.00675513 0.5407968338 -0.4618272530 -7.625720e-02 -0.177348616
## [132,] 1.30343896 -0.4607099296 0.2643065329 -3.356327e-02 -0.100342543
## [133,] 0.95838681 -0.4869393345 0.1881508451 -5.659957e-02 -0.072253726
## [134,] 1.18401500 -0.4471723939 0.2570614765 -3.016307e-02 -0.062315609
## [135,] 1.07458712 -0.3650636260 0.2546463208 -8.959202e-02 0.028826429
## [136,] 1.08937421 -0.3717038493 0.1205741859 -1.843713e-02 0.045760580
## [137,] -0.11183011 0.3043792045 -0.1516516077 -3.557179e-01 -0.032810349
## [138,] 0.20888553 -0.5275345677 0.1124609346 -5.930183e-01 0.376046862
## [139,] 0.47286002 0.1412503836 0.9606664322 5.895386e-02 0.130678757
## [140,] 0.67212442 -0.2671718542 0.3297977543 -3.097939e-01 0.003832633
## [141,] 0.28796809 0.2251490753 0.4384379673 1.275042e-01 0.208626132
## [142,] -0.02250288 -0.0922838655 0.6251372899 -1.162354e+00 0.168419794
## [143,] 0.34418432 -0.1711513228 -0.2189102391 -5.212920e-01 0.467973078
## [144,] 1.07654549 0.6940836506 -0.9243576757 -1.694764e-02 -0.137634393
## [145,] 0.93281684 -0.5228990290 0.2694356743 -3.070418e-01 -0.050356643
## [146,] -3.18443785 -0.7438540221 0.4066323700 1.583661e+00 0.575108123
## [147,] 1.06717252 -0.3397410076 0.2201744068 -9.358929e-02 0.024377222
## [148,] 0.80824332 -0.3302172553 0.1391921066 -1.604844e-01 -0.090258890
## [149,] 1.22430136 0.0871948598 -0.2591661155 4.019766e-02 -0.136947866
## [150,] 1.05447741 -0.1543326372 0.4536170345 5.211853e-02 -0.043550579
## [151,] 1.04333128 -0.2288550227 0.3594012592 -2.596068e-02 -0.035171898
## [152,] 0.84943798 -0.1035340420 0.5836853316 -1.020722e-01 -0.054543391
## [153,] 1.02940017 -0.1547998275 -0.1923899590 2.856667e-03 0.058902303
## [154,] 0.39707127 -0.0168057926 0.5788233217 -7.640874e-01 -0.066660671
## [155,] 1.38885601 -0.5690528884 0.2314207961 -2.124517e-02 -0.091789299
## [156,] -2.10534411 -0.8790908783 0.1196340531 4.951007e-01 -0.399152538
## [157,] -0.94690511 -0.3674869252 0.5395080461 7.169925e-01 -0.048400289
## [158,] 0.99393880 -0.0635048487 -0.2020406424 4.515528e-02 -0.065786576
## [159,] -0.28531006 -0.3541772263 0.2917156994 4.519864e-02 -0.031081093
## [160,] -1.03017136 -1.0361993602 -0.1707735459 2.128945e-01 -0.193738153
## [161,] -0.35485260 -0.3853783711 0.3230685951 5.594227e-01 0.157293084
## [162,] 1.14689210 0.0795306282 0.6088149730 1.928414e-01 -0.150608121
## [163,] 0.92036981 -0.1025116285 -0.0397713887 -1.145054e-02 0.113646494
## [164,] -3.05168162 -1.1166208170 -0.7159845011 1.537208e-01 -0.135355954
## [165,] -0.14994267 -0.3913717078 -0.2421719977 -2.766832e-01 -0.036986765
## [166,] -1.80878413 0.0566334496 -0.2422449984 3.512095e-02 0.230965549
## [167,] -0.54851470 0.0452361851 0.7101191669 3.068431e-01 -0.259912693
## [168,] 0.71052625 -0.4665092314 0.2733552116 -6.900412e-02 -0.132030137
## [169,] 1.24301618 -0.2889456013 0.1342404677 -9.451263e-03 -0.074195145
## [170,] 1.12716773 -0.0936776748 0.0446746742 8.243335e-02 0.015988183
## [171,] -0.90926104 -0.8317067060 -0.1998028894 -3.331411e-03 -0.147138197
## [172,] -3.27135965 0.4844985168 1.3117135113 -9.195516e-01 -0.175570118
## [173,] 0.20685284 -0.5580156466 0.2248068955 -1.338342e-01 -0.062418192
## [174,] -1.58573375 -1.0507762119 -0.2920206050 5.614834e-01 -0.069519512
## [175,] 0.83240063 0.0296716850 0.1511531426 2.142830e-01 0.216354135
## [176,] -0.53378209 -0.5059735509 0.4009604478 -1.696169e-02 0.110272790
## [177,] 0.23300367 0.4510780875 -0.8435857968 -3.784251e-01 0.091638181
## [178,] 0.34523774 0.2986179690 0.6309155013 -3.748515e-01 0.116635082
## [179,] 0.52247477 -0.3031257221 0.1815526848 -5.867474e-01 0.200947639
## [180,] 0.63766473 0.5699523520 0.1113244841 -1.763475e-01 -0.062042887
## [181,] 0.01290303 -0.0294551255 0.7374726259 1.485187e-02 0.263695260
## [182,] -3.32956183 3.6298166964 -0.2769640395 -1.248901e+00 0.071987331
## [183,] -0.68822721 -0.9146602969 -0.0990009318 -1.158184e-01 -0.344501680
## [184,] -7.47744667 15.7336154455 6.4071500330 1.566581e+00 -0.390933851
## [185,] 1.00703448 -0.6486837093 0.1682726870 5.514838e-02 0.204836624
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## [382,] 0.81131596 1.0058196043 -1.0577260590 -3.067384e-01 -0.107566207
## [383,] -0.12863861 0.3117748537 0.4582050708 -9.939952e-02 0.162220332
## [384,] 0.98212572 0.0222401601 -0.3036920467 4.719205e-02 0.066127080
## [385,] -1.64808006 1.1586559064 0.9605663032 -1.324026e+00 0.742990749
## [386,] 1.10233193 0.0088755009 0.0972514015 8.876743e-02 -0.053949151
## [387,] 0.82259230 -0.0935972530 0.1765052575 -1.786855e-01 0.008277633
## [388,] 1.04129188 -0.0912372095 0.1742296693 -3.926493e-02 -0.062097721
## [389,] 1.19768522 -0.2641713568 0.0789849464 -1.220946e-03 -0.064952858
## [390,] 1.09437876 -0.0030619385 -0.0478148524 -2.252481e-02 -0.068766279
## [391,] 1.06891237 0.4179833336 -0.3424848203 7.987405e-02 -0.108186282
## [392,] 0.88438236 -0.0417631467 0.5367800244 -3.089990e-02 -0.009649391
## [393,] 0.79981986 -0.3397531358 0.2968846699 -2.819700e-01 0.110441519
## [394,] 0.48759544 0.8695421826 -0.8090023384 -4.435117e-01 0.028695796
## [395,] 1.07628493 -0.3243979663 0.1054144579 6.200560e-02 0.097367055
## [396,] 1.08292394 -0.1408151659 -0.1508761886 -5.685268e-03 -0.156053509
## [397,] -0.65441107 0.1365619541 0.2609186633 -5.374683e-01 -0.017928094
## [398,] 1.06672699 0.5739678319 -0.5833083159 -5.032264e-03 -0.068046024
## [399,] 1.21812567 0.2573167088 -0.4850298560 -3.179681e-02 -0.108576616
## [400,] 1.20418087 -0.2977446541 0.0719496515 3.635687e-02 -0.118696408
## [401,] 1.12755720 0.1486469749 -0.0539299714 7.907698e-02 -0.080788486
## [402,] 0.78619937 1.7607701632 -1.2401567867 8.773626e-02 -0.092231125
## [403,] 0.70963764 -0.4824173163 0.2787551961 -3.455904e-01 0.247948235
## [404,] 0.21181784 -0.4378501159 0.3382349083 -1.023084e+00 0.087221718
## [405,] 0.65039342 0.1682494910 -0.2479710243 -2.358100e-01 -0.038949793
## [406,] 1.13695208 -0.2329491833 0.0020048404 5.289853e-03 -0.124123853
## [407,] 0.43799628 0.9861577681 -1.0141918729 -1.341328e-01 0.017341293
## [408,] -1.67259278 -0.5997607604 -0.4539003847 -1.927750e-01 0.088799367
## [409,] 0.36550163 -0.4654167058 -0.0653570248 4.368427e-03 -0.044121872
## [410,] 0.05904374 0.7407264885 0.9812353376 5.321543e-01 -0.116912163
## [411,] 0.58114647 -0.1053616044 0.3728519656 2.555079e-01 -0.091531240
## [412,] 0.54871526 0.5993113197 1.0280690648 2.474061e-01 -0.033336374
## [413,] 0.02754893 -0.8683954018 0.0009452655 2.004207e-01 0.396172149
## [414,] 0.18022987 2.4627986053 -1.8610262286 1.696222e-01 0.081699407
## [415,] 0.84472130 0.2166544351 -0.5858918678 3.730761e-02 -0.052819470
## [416,] -0.15011103 -0.1654789686 0.2521128931 6.515206e-02 -0.052293459
## [417,] -0.94319868 -0.6282524920 0.0694434201 -2.856556e-01 -0.328750555
## [418,] -0.17681577 -0.5846549679 0.2174968459 9.846607e-02 0.179411157
## [419,] -1.21247875 -0.9451190928 -0.0111536007 2.085788e-01 0.281727286
## [420,] 0.67045226 -0.2169645295 0.4594481571 -7.930226e-02 -0.225166310
## [421,] -0.70505273 -0.7893865579 0.1792825081 4.685864e-01 -0.138527213
## [422,] -0.06490484 -0.3007384881 0.3109499418 1.898877e-01 0.016876618
## [423,] 0.82591686 -0.2892677213 0.3292781858 1.754135e-01 0.035366768
## [424,] 0.57180936 -0.3995984651 0.1544486982 -6.623976e-02 -0.049472294
## [425,] 0.04046836 -0.7367264203 -0.0847164943 3.219454e-01 0.343336774
## [426,] 0.76883248 2.0500342258 -1.5657601158 1.670196e-01 -0.067827419
## [427,] -0.93848842 -0.0821362098 -0.0534415939 1.076078e-02 0.138959378
## [428,] -0.43132555 2.0067711242 -1.5734003459 -1.398859e+00 0.039329073
## [429,] 0.51934102 -0.2273851246 -0.0315692426 -4.106207e-01 0.096672075
## [430,] 0.83217183 -0.0517546591 0.7913966759 1.911758e-01 0.080207639
## [431,] -0.12732308 -0.2510251070 0.4661498794 3.030175e-01 1.035711609
## [432,] 0.28430937 1.6278170123 -1.4322862099 -6.732602e-02 -0.051096480
## [433,] 0.83664364 -0.5884685158 0.1925679473 1.462679e-01 0.052584928
## [434,] 0.89763536 -0.0286593561 0.3618008079 -1.269600e-01 -0.105069502
## [435,] 0.27267232 -0.4987640539 0.1838051451 7.266804e-02 0.119401988
## [436,] -0.78171970 1.7262064236 -1.2339946527 -4.534560e-01 0.892440952
## [437,] 1.00383404 0.6000966110 0.1372499975 1.617472e-01 -0.153667550
## [438,] -3.47543102 -1.2015869428 -0.1938524404 5.134742e-01 -0.065875377
## [439,] 0.91187529 0.0286815529 0.5761825595 9.421507e-02 -0.030771798
## [440,] 1.06427400 -0.6008476585 0.2126003922 -8.899895e-02 0.011009682
plot(wholesale_pca$x,xlim=xlim,ylim=xlim)
wholesale_pca$rotation[,1]
## Milk Grocery Frozen Detergents_Paper
## -0.54363795 -0.58193330 -0.03962544 -0.55369302
## Delicassen
## -0.24013597
wholesale_pca$rotation
## PC1 PC2 PC3 PC4 PC5
## Milk -0.54363795 0.1146154 0.09014458 -0.82543534 -0.04302952
## Grocery -0.58193330 -0.1556719 -0.12777739 0.30993371 0.72438520
## Frozen -0.03962544 0.7024176 -0.70857828 0.04761674 -0.02624427
## Detergents_Paper -0.55369302 -0.2718776 -0.19028739 0.34173928 -0.68301653
## Delicassen -0.24013597 0.6287461 0.66125216 0.32178331 -0.07883018
plot(wholesale[,-1])
wholesale_pca$x
## PC1 PC2 PC3 PC4 PC5
## [1,] -0.19707283 -0.3770084356 0.4339928374 -5.086349e-01 -0.001854585
## [2,] -0.45313294 -0.1211597823 0.2609418663 -3.508749e-01 0.040946165
## [3,] -0.81180172 1.3273282020 1.5940953009 4.144155e-01 -0.301861199
## [4,] 0.79342916 0.6658443374 -0.3359082992 2.853570e-01 0.057266232
## [5,] -0.11570147 1.0073354473 0.7846578714 3.653701e-01 -0.003812347
## [6,] 0.14370629 -0.2180994333 0.4452745197 -4.774821e-01 -0.059000770
## [7,] 0.32567049 -0.6325704892 0.1196417115 1.399425e-01 -0.054904769
## [8,] -0.15665440 -0.0331363080 0.4012580200 2.786108e-01 0.032831032
## [9,] 0.48890741 -0.4938233270 0.2485820432 -1.502553e-02 0.081354092
## [10,] -1.62027497 -0.5048683883 0.1499964109 1.363545e-01 0.145687282
## [11,] -0.66758413 -0.0238881161 -0.3383420998 4.676957e-01 -0.071596678
## [12,] 0.92597350 -0.3515756476 0.0822191593 1.100768e-01 0.137720104
## [13,] -0.92658585 -0.1074909163 0.7247966859 -4.006276e-01 0.084630659
## [14,] -0.82672223 -0.5293360636 -0.4619419906 3.523687e-01 0.011172418
## [15,] -0.80858534 -0.3934991730 0.4585439002 -7.316764e-02 -0.020590692
## [16,] 0.93709140 -0.5308636604 0.2043574976 9.831297e-02 0.032723673
## [17,] -0.60479469 -0.6384278916 0.2404058097 -1.647392e-01 0.095547612
## [18,] 0.33914993 0.5663431002 1.1904730227 -6.896284e-02 -0.095319576
## [19,] -0.29126066 0.2233895662 0.4970352941 1.829471e-01 0.135411974
## [20,] 0.29954840 -0.6312712075 0.0644977021 2.521058e-01 0.228237979
## [21,] 0.33682556 -0.0861339420 0.4875413015 3.768933e-02 -0.164582644
## [22,] 1.09654804 -0.0043401285 -0.1497704508 7.141227e-02 -0.040058284
## [23,] 0.26619036 1.5683970175 -0.2467060883 6.670989e-01 -0.283900004
## [24,] -4.58054505 3.8072871727 3.3396697767 -1.130469e+00 0.254755186
## [25,] -1.19755447 0.8003953225 0.9263685687 3.438610e-01 0.074691495
## [26,] 0.15537156 -0.8250948908 0.0157524281 4.829123e-02 -0.122135167
## [27,] 1.03266607 0.0159926101 -0.0590410608 1.074156e-01 0.037212525
## [28,] 1.09811094 -0.4373483299 0.2574858397 5.881782e-02 0.095718884
## [29,] -3.14687957 0.1506165427 0.8514050232 -2.440491e-01 0.374539040
## [30,] 0.88052223 -0.2960335906 0.2061557803 1.353125e-02 -0.101725549
## [31,] -0.05215116 -0.0007608697 0.5787210362 4.390835e-01 0.330576240
## [32,] 0.69579690 -0.0888786625 0.1462865658 -2.131695e-01 -0.043052084
## [33,] 0.98632753 -0.5302711469 0.2387360039 3.962267e-02 -0.032243165
## [34,] 0.41807632 0.4822328908 -0.4532962679 -1.084847e-01 0.315119579
## [35,] 1.02591988 -0.4642031406 0.2470086458 -8.541622e-02 -0.021926123
## [36,] -0.21643153 -0.7002955975 -0.0286492746 8.763578e-02 0.089179114
## [37,] 0.24158323 0.6313110592 1.0201656795 2.740459e-01 0.025899292
## [38,] -0.97020398 -0.5543555171 -0.1693693299 -2.287695e-01 -0.173107471
## [39,] -1.62332525 -0.9046825507 0.0284863528 -6.876237e-01 0.072911071
## [40,] 0.95272626 1.4991601790 -0.5480032712 3.916575e-01 -0.200711189
## [41,] 0.08308879 2.0275377344 0.1721111919 4.933808e-01 -0.142283907
## [42,] 0.25869103 0.1421617102 0.4567992931 3.539627e-01 -0.122343929
## [43,] -0.87588116 -1.0635936007 -0.1589398770 1.228399e-01 0.005470463
## [44,] -2.00255094 -1.2141592087 -0.4235084566 2.189990e-01 0.292958699
## [45,] -0.30164586 -0.8128614625 -0.0610496539 -1.224052e-01 -0.009380470
## [46,] -2.83141245 0.3536181366 0.8431308911 -6.720454e-01 0.210311577
## [47,] -1.90336183 -0.5432914831 -0.0554886874 -2.103213e-01 0.468640242
## [48,] -9.41725404 0.5414621846 -0.4271519661 -1.731283e+00 0.133925231
## [49,] -0.44041724 -0.5408300715 0.2274220164 1.858785e-01 -0.085748415
## [50,] -3.63590895 -0.9762339518 -0.4172346295 -3.493400e-01 -0.008648759
## [51,] 0.91517116 0.4104644981 0.1479309633 2.485985e-01 -0.124280227
## [52,] 0.47041131 -0.6176023581 0.1716656472 -9.969138e-02 0.179345625
## [53,] 0.34153413 -0.4009520531 0.3295290114 6.842046e-02 -0.084407972
## [54,] -0.75096260 -0.7685290601 -0.0652044882 -3.819017e-01 -0.096389717
## [55,] 1.02036283 0.0487333009 0.1823242891 7.034276e-02 -0.039970438
## [56,] 0.48573185 -0.3152336743 0.2495333559 1.398177e-02 -0.067490936
## [57,] -4.63920836 -0.8901055110 -0.5298270393 -1.038605e+00 -0.819611828
## [58,] -0.95925425 -0.7378871248 0.2151100896 -1.012359e-01 -0.479576833
## [59,] 1.08902399 -0.4058042205 0.2500262845 -1.164280e-01 -0.034073572
## [60,] 0.02055344 -0.4281666899 0.4332603258 4.625049e-02 -0.005978029
## [61,] 0.20266611 -0.8307229912 0.0488423661 2.140045e-01 -0.112791726
## [62,] -8.37149191 -1.5623789638 -1.1584129243 -1.933842e-01 0.319907948
## [63,] -0.04643766 -0.0064623816 -0.3126388497 -6.399385e-02 -0.270890553
## [64,] -1.44256223 -0.3881746020 -0.2539083496 -7.828486e-02 -0.117075631
## [65,] 0.84129649 0.1089106750 -0.1116094122 2.036070e-01 -0.090476223
## [66,] -5.88216805 -2.0643796924 -0.7569200156 1.028312e+00 -0.240375986
## [67,] 0.42975520 -0.8439903706 0.0033292780 3.019871e-01 -0.042364665
## [68,] -0.59711484 -0.6209401671 -0.0494590712 1.373610e-01 0.119889933
## [69,] 0.22115034 0.9618614565 0.1144127302 -2.362520e-01 -0.069370103
## [70,] 1.02170230 -0.4498752241 0.1528820924 -2.238458e-01 -0.120372633
## [71,] 0.84070633 1.2369213016 -1.0142299556 1.233516e-01 0.019609630
## [72,] -1.73915275 2.8610779436 2.4170622052 2.526060e+00 0.464898413
## [73,] 0.62067938 0.7050255622 -1.0362899361 -3.073257e-01 -0.169665352
## [74,] 0.26682334 0.6376948170 -0.8755662868 -1.254282e-01 0.361266482
## [75,] -0.04638691 -0.1674522707 0.3416721379 -5.974311e-02 0.280263771
## [76,] 1.20012549 0.2925598478 -0.1589521213 5.912953e-03 -0.158188044
## [77,] 0.54017219 0.6274661824 -0.7126274387 3.926234e-03 0.235234832
## [78,] -2.77004981 -1.1857563171 -0.3572508458 4.752266e-01 0.244348076
## [79,] 1.12399443 -0.2721741808 -0.0502825534 -2.452565e-02 -0.008690418
## [80,] 0.65209963 -0.1635736239 0.4455307307 1.627898e-02 -0.063766052
## [81,] 1.03868601 -0.4709420234 0.2485400502 9.200612e-02 0.019753232
## [82,] -1.10479248 -1.0377605203 -0.1519433582 -3.801156e-02 -0.183875803
## [83,] -0.56696336 -0.1897705085 0.5070899455 -1.672162e-01 0.108922971
## [84,] 1.03054389 -0.1083993421 0.0575018685 1.189421e-02 -0.086393476
## [85,] 0.39812160 -0.6286896384 -0.0790878932 6.345882e-02 -0.312116534
## [86,] -12.68123458 -2.9055675082 -1.5301790149 1.109718e+00 0.766109027
## [87,] -8.39266413 -0.7648749958 -0.0254756094 -5.643262e+00 -0.986574914
## [88,] -0.92068706 3.3879831694 2.5748630597 1.493591e+00 -0.172326436
## [89,] 1.01342557 0.7716998749 -1.2224864249 1.620546e-01 0.127114509
## [90,] 0.44301966 0.5731766717 0.4416464506 1.520250e-01 0.111153688
## [91,] 1.19321062 -0.0368736054 -0.1796662555 4.390303e-02 -0.016938275
## [92,] 0.80614475 0.8926142932 -0.7902658775 9.552051e-03 -0.091570032
## [93,] -5.24057761 -0.1447202035 0.1233521218 -7.733263e-02 -0.687874557
## [94,] 0.52578694 5.0971997130 -4.2280974876 3.562690e-01 -0.235963847
## [95,] -0.79761716 -0.7786843800 0.0650273452 -6.281708e-01 -0.038072173
## [96,] 0.71560919 -0.4279470962 0.2866668376 -4.319073e-02 0.305115990
## [97,] 0.24404605 -0.8238016100 0.0398452920 2.543221e-01 -0.058548989
## [98,] 1.32938626 -0.4629908981 0.1364874089 -1.157487e-02 -0.068943918
## [99,] 1.32246301 -0.4351711891 0.1309323486 1.898908e-02 -0.058179488
## [100,] 1.02727861 0.2983698332 -0.5129768013 -9.591612e-02 -0.037799311
## [101,] -1.13082005 0.0296427973 0.0885664798 4.577611e-01 -0.473247863
## [102,] -1.34423210 -0.4240373165 0.0836781087 1.010917e-02 0.047409545
## [103,] -0.21246138 -0.1865573632 -0.0137137578 1.731627e-02 -0.260442905
## [104,] 0.06820127 2.4096180816 -1.9396808134 4.447883e-01 0.178855067
## [105,] 0.80468449 -0.3727619490 0.0956486645 3.469641e-02 -0.086245320
## [106,] 0.94469735 -0.1982170834 0.3856879072 1.704796e-01 0.133073495
## [107,] -0.66901612 -0.6188300049 0.3127463650 3.184159e-01 -0.351635129
## [108,] -1.47652662 -0.4917273047 -0.2096213973 1.042837e-01 -0.366056895
## [109,] -0.04077613 -0.3953887590 0.4044253759 -4.101700e-01 -0.011842382
## [110,] -1.70666698 -0.7445501815 -0.0743597119 -8.805089e-01 1.888181050
## [111,] 0.99983015 0.1048203863 0.2865328374 7.158538e-02 -0.063314112
## [112,] -1.37687414 -0.6081606384 0.1224336064 -4.770345e-02 0.202325530
## [113,] 0.68923179 1.2798147189 -0.4339000015 1.794542e-01 -0.120975838
## [114,] 0.90109151 0.2079202525 0.1193587893 2.975898e-02 -0.126406650
## [115,] 1.05901888 0.0493188652 0.1474579566 1.006991e-01 -0.020229691
## [116,] 1.05586310 -0.1034380740 -0.0528084643 1.030625e-01 0.051592527
## [117,] 0.94497402 -0.3443957553 0.0458862013 -1.318167e-01 0.081944110
## [118,] 0.63888952 -0.1290378910 0.2358638727 -1.088179e-01 0.200165919
## [119,] 0.94868598 0.3684258484 -0.3442094906 3.215203e-02 -0.045101450
## [120,] 0.98250864 0.1114467083 -0.1886718345 -8.411286e-02 -0.027206760
## [121,] 0.96940760 -0.0240916571 0.1173633154 1.211556e-01 0.083059013
## [122,] 1.00153477 -0.1658860503 -0.0390138016 -2.630435e-01 -0.062843175
## [123,] 1.28120984 -0.1024026325 0.1511531050 8.324730e-02 -0.121160465
## [124,] -0.18913115 -0.3203897860 -0.1106006465 -7.592123e-01 0.209858651
## [125,] 0.86596557 0.4226150095 -0.1163835099 1.589650e-01 -0.026966052
## [126,] 0.40917867 1.9108688107 -2.0407836107 1.442061e-01 0.194309814
## [127,] 1.01779186 0.6950263922 -0.8546792729 -1.292082e-02 -0.092424266
## [128,] -0.30277111 -0.0382865069 0.6076499875 1.001440e-02 0.248558255
## [129,] 0.39288434 -0.5444758971 0.2361887980 -8.086403e-01 -0.013436955
## [130,] 1.02620109 0.0404906424 0.3923445875 1.777608e-01 -0.109445886
## [131,] 1.00675513 0.5407968338 -0.4618272530 -7.625720e-02 -0.177348616
## [132,] 1.30343896 -0.4607099296 0.2643065329 -3.356327e-02 -0.100342543
## [133,] 0.95838681 -0.4869393345 0.1881508451 -5.659957e-02 -0.072253726
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## [331,] 0.81990469 0.1028458245 -0.0887119701 1.122326e-01 0.204217975
## [332,] -2.55569469 -0.9119772593 -0.2422695809 1.565106e-02 0.445203963
## [333,] 0.81764691 0.3357835077 0.5424978555 -2.891576e-03 -0.118900424
## [334,] -7.61379702 -3.4878261273 -1.8570054614 4.487063e+00 -0.492430881
## [335,] 0.73733540 1.8203153674 -0.6665945815 4.988941e-01 -0.104095182
## [336,] -0.43016311 -0.2108130517 0.3183683323 1.198782e-01 0.026361034
## [337,] 1.12215088 -0.3190418064 0.3242381916 -4.171648e-02 -0.053885459
## [338,] 0.95236916 0.7486749232 -0.7833034255 1.236485e-01 -0.040856249
## [339,] 0.77302224 1.6893212630 -1.9971202384 3.868789e-01 0.331097800
## [340,] 0.67925139 1.1382025886 -0.7816151404 3.759789e-01 0.111049057
## [341,] -0.44952190 -0.7286057941 0.1357307410 5.248944e-01 -0.468668348
## [342,] -0.49874907 -0.3767392711 0.3492630012 3.240041e-01 -0.081203551
## [343,] -0.03297929 -0.5029489774 0.3096893528 1.177555e-02 -0.379628062
## [344,] -2.53250139 -1.5660071985 -0.8480530559 1.184938e+00 -0.359835221
## [345,] 1.13340753 -0.1952182547 -0.0133121117 -1.458200e-02 -0.026484205
## [346,] 0.22596844 -0.7694471361 0.0206476758 2.730768e-01 -0.041278788
## [347,] -0.94277386 -0.4648303557 -0.2772970552 3.357660e-01 0.052682251
## [348,] -0.52623469 -0.2992166497 -0.1906294560 5.170232e-02 0.090517992
## [349,] 0.89883641 -0.3013837867 0.1566870505 -4.785936e-02 -0.155021430
## [350,] -2.40481023 -0.9960767917 -0.5310822389 -4.374715e-02 -0.394974382
## [351,] 1.08068712 -0.1237118941 0.1927739106 6.405186e-02 -0.016769761
## [352,] -2.45061408 -0.5584735441 0.0419149034 8.628946e-01 -0.367013462
## [353,] 1.19422964 -0.4293999671 0.1558240037 -5.857045e-02 -0.012704664
## [354,] -1.46109306 -1.0443346120 -0.0859166808 7.205129e-01 0.203389284
## [355,] 0.29654054 0.8630742744 -0.1383954212 -3.401633e-01 -0.240078342
## [356,] 1.19246382 -0.5482961618 0.2104436785 -7.319833e-03 0.017614488
## [357,] 1.30670647 -0.0029419227 -0.0920076981 6.454974e-02 -0.118117924
## [358,] -0.84837304 -1.2653251323 -0.3054295861 1.059554e+00 0.619631964
## [359,] -0.53430822 1.4509195863 0.4951650461 -1.488780e+00 -0.307004553
## [360,] 0.74548879 -0.3141877231 0.4084485713 -5.018286e-01 -0.030554517
## [361,] 0.95060230 -0.1063642743 -0.0303243494 -1.610490e-01 -0.059279836
## [362,] 1.24298882 -0.3289021623 0.1503307078 8.015338e-03 -0.078577675
## [363,] 1.04927604 -0.3656586146 0.3065814927 -2.120530e-02 0.028795306
## [364,] 0.87486904 -0.6155984555 0.1869141366 1.449102e-01 0.031142672
## [365,] 1.13722957 -0.3566829731 0.1603429922 3.141357e-02 -0.081879125
## [366,] -0.34134077 0.0528651642 0.5204387607 2.484323e-01 -0.266636410
## [367,] 1.06478454 -0.3160073629 0.1713890889 -1.369749e-01 -0.037004496
## [368,] 1.23457189 -0.3020715155 0.1031540306 -3.290657e-02 -0.118323974
## [369,] 1.09202865 -0.1860571487 0.0523766298 1.397055e-02 0.035019264
## [370,] 1.29790056 -0.3646317914 0.1456950323 1.026699e-02 -0.070216959
## [371,] 0.54728205 0.0660108492 0.5275880023 4.670435e-03 0.109653457
## [372,] 0.92861428 0.7341864175 -0.7960212484 5.201769e-02 -0.132267223
## [373,] 0.55848361 0.6329891063 1.2548922421 1.947481e-01 -0.193946445
## [374,] -0.01036762 0.1984867185 0.6528332213 2.705561e-02 0.057534446
## [375,] 1.02837629 -0.2211011595 0.1777392160 -1.044276e-01 -0.058081877
## [376,] 1.15932849 -0.5015726865 0.1543070714 -9.802522e-02 -0.093532531
## [377,] -0.77356526 0.1996188872 -0.5105311814 8.662076e-03 0.146226030
## [378,] 0.88358086 -0.1532556029 0.3813297561 -1.293612e-01 0.029117565
## [379,] 0.93923945 -0.2746083703 0.4739350118 -1.933370e-01 -0.016908645
## [380,] 0.27600519 -0.6575609068 0.1558497541 -1.804023e-01 0.539501791
## [381,] 1.07810889 -0.0128717819 -0.3024832323 5.457804e-02 -0.056683715
## [382,] 0.81131596 1.0058196043 -1.0577260590 -3.067384e-01 -0.107566207
## [383,] -0.12863861 0.3117748537 0.4582050708 -9.939952e-02 0.162220332
## [384,] 0.98212572 0.0222401601 -0.3036920467 4.719205e-02 0.066127080
## [385,] -1.64808006 1.1586559064 0.9605663032 -1.324026e+00 0.742990749
## [386,] 1.10233193 0.0088755009 0.0972514015 8.876743e-02 -0.053949151
## [387,] 0.82259230 -0.0935972530 0.1765052575 -1.786855e-01 0.008277633
## [388,] 1.04129188 -0.0912372095 0.1742296693 -3.926493e-02 -0.062097721
## [389,] 1.19768522 -0.2641713568 0.0789849464 -1.220946e-03 -0.064952858
## [390,] 1.09437876 -0.0030619385 -0.0478148524 -2.252481e-02 -0.068766279
## [391,] 1.06891237 0.4179833336 -0.3424848203 7.987405e-02 -0.108186282
## [392,] 0.88438236 -0.0417631467 0.5367800244 -3.089990e-02 -0.009649391
## [393,] 0.79981986 -0.3397531358 0.2968846699 -2.819700e-01 0.110441519
## [394,] 0.48759544 0.8695421826 -0.8090023384 -4.435117e-01 0.028695796
## [395,] 1.07628493 -0.3243979663 0.1054144579 6.200560e-02 0.097367055
## [396,] 1.08292394 -0.1408151659 -0.1508761886 -5.685268e-03 -0.156053509
## [397,] -0.65441107 0.1365619541 0.2609186633 -5.374683e-01 -0.017928094
## [398,] 1.06672699 0.5739678319 -0.5833083159 -5.032264e-03 -0.068046024
## [399,] 1.21812567 0.2573167088 -0.4850298560 -3.179681e-02 -0.108576616
## [400,] 1.20418087 -0.2977446541 0.0719496515 3.635687e-02 -0.118696408
## [401,] 1.12755720 0.1486469749 -0.0539299714 7.907698e-02 -0.080788486
## [402,] 0.78619937 1.7607701632 -1.2401567867 8.773626e-02 -0.092231125
## [403,] 0.70963764 -0.4824173163 0.2787551961 -3.455904e-01 0.247948235
## [404,] 0.21181784 -0.4378501159 0.3382349083 -1.023084e+00 0.087221718
## [405,] 0.65039342 0.1682494910 -0.2479710243 -2.358100e-01 -0.038949793
## [406,] 1.13695208 -0.2329491833 0.0020048404 5.289853e-03 -0.124123853
## [407,] 0.43799628 0.9861577681 -1.0141918729 -1.341328e-01 0.017341293
## [408,] -1.67259278 -0.5997607604 -0.4539003847 -1.927750e-01 0.088799367
## [409,] 0.36550163 -0.4654167058 -0.0653570248 4.368427e-03 -0.044121872
## [410,] 0.05904374 0.7407264885 0.9812353376 5.321543e-01 -0.116912163
## [411,] 0.58114647 -0.1053616044 0.3728519656 2.555079e-01 -0.091531240
## [412,] 0.54871526 0.5993113197 1.0280690648 2.474061e-01 -0.033336374
## [413,] 0.02754893 -0.8683954018 0.0009452655 2.004207e-01 0.396172149
## [414,] 0.18022987 2.4627986053 -1.8610262286 1.696222e-01 0.081699407
## [415,] 0.84472130 0.2166544351 -0.5858918678 3.730761e-02 -0.052819470
## [416,] -0.15011103 -0.1654789686 0.2521128931 6.515206e-02 -0.052293459
## [417,] -0.94319868 -0.6282524920 0.0694434201 -2.856556e-01 -0.328750555
## [418,] -0.17681577 -0.5846549679 0.2174968459 9.846607e-02 0.179411157
## [419,] -1.21247875 -0.9451190928 -0.0111536007 2.085788e-01 0.281727286
## [420,] 0.67045226 -0.2169645295 0.4594481571 -7.930226e-02 -0.225166310
## [421,] -0.70505273 -0.7893865579 0.1792825081 4.685864e-01 -0.138527213
## [422,] -0.06490484 -0.3007384881 0.3109499418 1.898877e-01 0.016876618
## [423,] 0.82591686 -0.2892677213 0.3292781858 1.754135e-01 0.035366768
## [424,] 0.57180936 -0.3995984651 0.1544486982 -6.623976e-02 -0.049472294
## [425,] 0.04046836 -0.7367264203 -0.0847164943 3.219454e-01 0.343336774
## [426,] 0.76883248 2.0500342258 -1.5657601158 1.670196e-01 -0.067827419
## [427,] -0.93848842 -0.0821362098 -0.0534415939 1.076078e-02 0.138959378
## [428,] -0.43132555 2.0067711242 -1.5734003459 -1.398859e+00 0.039329073
## [429,] 0.51934102 -0.2273851246 -0.0315692426 -4.106207e-01 0.096672075
## [430,] 0.83217183 -0.0517546591 0.7913966759 1.911758e-01 0.080207639
## [431,] -0.12732308 -0.2510251070 0.4661498794 3.030175e-01 1.035711609
## [432,] 0.28430937 1.6278170123 -1.4322862099 -6.732602e-02 -0.051096480
## [433,] 0.83664364 -0.5884685158 0.1925679473 1.462679e-01 0.052584928
## [434,] 0.89763536 -0.0286593561 0.3618008079 -1.269600e-01 -0.105069502
## [435,] 0.27267232 -0.4987640539 0.1838051451 7.266804e-02 0.119401988
## [436,] -0.78171970 1.7262064236 -1.2339946527 -4.534560e-01 0.892440952
## [437,] 1.00383404 0.6000966110 0.1372499975 1.617472e-01 -0.153667550
## [438,] -3.47543102 -1.2015869428 -0.1938524404 5.134742e-01 -0.065875377
## [439,] 0.91187529 0.0286815529 0.5761825595 9.421507e-02 -0.030771798
## [440,] 1.06427400 -0.6008476585 0.2126003922 -8.899895e-02 0.011009682
plot(wholesale_pca)
#get the original value of the data based on PCA
center <- wholesale_pca$center
scale <- wholesale_pca$scale
new_wholesale <- as.matrix(wholesale[,-1])
new_wholesale
## Fresh Milk Grocery Frozen Detergents_Paper Delicassen
## [1,] 12669 9656 7561 214 2674 1338
## [2,] 7057 9810 9568 1762 3293 1776
## [3,] 6353 8808 7684 2405 3516 7844
## [4,] 13265 1196 4221 6404 507 1788
## [5,] 22615 5410 7198 3915 1777 5185
## [6,] 9413 8259 5126 666 1795 1451
## [7,] 12126 3199 6975 480 3140 545
## [8,] 7579 4956 9426 1669 3321 2566
## [9,] 5963 3648 6192 425 1716 750
## [10,] 6006 11093 18881 1159 7425 2098
## [11,] 3366 5403 12974 4400 5977 1744
## [12,] 13146 1124 4523 1420 549 497
## [13,] 31714 12319 11757 287 3881 2931
## [14,] 21217 6208 14982 3095 6707 602
## [15,] 24653 9465 12091 294 5058 2168
## [16,] 10253 1114 3821 397 964 412
## [17,] 1020 8816 12121 134 4508 1080
## [18,] 5876 6157 2933 839 370 4478
## [19,] 18601 6327 10099 2205 2767 3181
## [20,] 7780 2495 9464 669 2518 501
## [21,] 17546 4519 4602 1066 2259 2124
## [22,] 5567 871 2010 3383 375 569
## [23,] 31276 1917 4469 9408 2381 4334
## [24,] 26373 36423 22019 5154 4337 16523
## [25,] 22647 9776 13792 2915 4482 5778
## [26,] 16165 4230 7595 201 4003 57
## [27,] 9898 961 2861 3151 242 833
## [28,] 14276 803 3045 485 100 518
## [29,] 4113 20484 25957 1158 8604 5206
## [30,] 43088 2100 2609 1200 1107 823
## [31,] 18815 3610 11107 1148 2134 2963
## [32,] 2612 4339 3133 2088 820 985
## [33,] 21632 1318 2886 266 918 405
## [34,] 29729 4786 7326 6130 361 1083
## [35,] 1502 1979 2262 425 483 395
## [36,] 688 5491 11091 833 4239 436
## [37,] 29955 4362 5428 1729 862 4626
## [38,] 15168 10556 12477 1920 6506 714
## [39,] 4591 15729 16709 33 6956 433
## [40,] 56159 555 902 10002 212 2916
## [41,] 24025 4332 4757 9510 1145 5864
## [42,] 19176 3065 5956 2033 2575 2802
## [43,] 10850 7555 14961 188 6899 46
## [44,] 630 11095 23998 787 9529 72
## [45,] 9670 7027 10471 541 4618 65
## [46,] 5181 22044 21531 1740 7353 4985
## [47,] 3103 14069 21955 1668 6792 1452
## [48,] 44466 54259 55571 7782 24171 6465
## [49,] 11519 6152 10868 584 5121 1476
## [50,] 4967 21412 28921 1798 13583 1163
## [51,] 6269 1095 1980 3860 609 2162
## [52,] 3347 4051 6996 239 1538 301
## [53,] 40721 3916 5876 532 2587 1278
## [54,] 491 10473 11532 744 5611 224
## [55,] 27329 1449 1947 2436 204 1333
## [56,] 5264 3683 5005 1057 2024 1130
## [57,] 4098 29892 26866 2616 17740 1340
## [58,] 5417 9933 10487 38 7572 1282
## [59,] 13779 1970 1648 596 227 436
## [60,] 6137 5360 8040 129 3084 1603
## [61,] 8590 3045 7854 96 4095 225
## [62,] 35942 38369 59598 3254 26701 2017
## [63,] 7823 6245 6544 4154 4074 964
## [64,] 9396 11601 15775 2896 7677 1295
## [65,] 4760 1227 3250 3724 1247 1145
## [66,] 85 20959 45828 36 24231 1423
## [67,] 9 1534 7417 175 3468 27
## [68,] 19913 6759 13462 1256 5141 834
## [69,] 2446 7260 3993 5870 788 3095
## [70,] 8352 2820 1293 779 656 144
## [71,] 16705 2037 3202 10643 116 1365
## [72,] 18291 1266 21042 5373 4173 14472
## [73,] 4420 5139 2661 8872 1321 181
## [74,] 19899 5332 8713 8132 764 648
## [75,] 8190 6343 9794 1285 1901 1780
## [76,] 20398 1137 3 4407 3 975
## [77,] 717 3587 6532 7530 529 894
## [78,] 12205 12697 28540 869 12034 1009
## [79,] 10766 1175 2067 2096 301 167
## [80,] 1640 3259 3655 868 1202 1653
## [81,] 7005 829 3009 430 610 529
## [82,] 219 9540 14403 283 7818 156
## [83,] 10362 9232 11009 737 3537 2342
## [84,] 20874 1563 1783 2320 550 772
## [85,] 11867 3327 4814 1178 3837 120
## [86,] 16117 46197 92780 1026 40827 2944
## [87,] 22925 73498 32114 987 20070 903
## [88,] 43265 5025 8117 6312 1579 14351
## [89,] 7864 542 4042 9735 165 46
## [90,] 24904 3836 5330 3443 454 3178
## [91,] 11405 596 1638 3347 69 360
## [92,] 12754 2762 2530 8693 627 1117
## [93,] 9198 27472 32034 3232 18906 5130
## [94,] 11314 3090 2062 35009 71 2698
## [95,] 5626 12220 11323 206 5038 244
## [96,] 3 2920 6252 440 223 709
## [97,] 23 2616 8118 145 3874 217
## [98,] 403 254 610 774 54 63
## [99,] 503 112 778 895 56 132
## [100,] 9658 2182 1909 5639 215 323
## [101,] 11594 7779 12144 3252 8035 3029
## [102,] 1420 10810 16267 1593 6766 1838
## [103,] 2932 6459 7677 2561 4573 1386
## [104,] 56082 3504 8906 18028 1480 2498
## [105,] 14100 2132 3445 1336 1491 548
## [106,] 15587 1014 3970 910 139 1378
## [107,] 1454 6337 10704 133 6830 1831
## [108,] 8797 10646 14886 2471 8969 1438
## [109,] 1531 8397 6981 247 2505 1236
## [110,] 1406 16729 28986 673 836 3
## [111,] 11818 1648 1694 2276 169 1647
## [112,] 12579 11114 17569 805 6457 1519
## [113,] 19046 2770 2469 8853 483 2708
## [114,] 14438 2295 1733 3220 585 1561
## [115,] 18044 1080 2000 2555 118 1266
## [116,] 11134 793 2988 2715 276 610
## [117,] 11173 2521 3355 1517 310 222
## [118,] 6990 3880 5380 1647 319 1160
## [119,] 20049 1891 2362 5343 411 933
## [120,] 8258 2344 2147 3896 266 635
## [121,] 17160 1200 3412 2417 174 1136
## [122,] 4020 3234 1498 2395 264 255
## [123,] 12212 201 245 1991 25 860
## [124,] 11170 10769 8814 2194 1976 143
## [125,] 36050 1642 2961 4787 500 1621
## [126,] 76237 3473 7102 16538 778 918
## [127,] 19219 1840 1658 8195 349 483
## [128,] 21465 7243 10685 880 2386 2749
## [129,] 140 8847 3823 142 1062 3
## [130,] 42312 926 1510 1718 410 1819
## [131,] 7149 2428 699 6316 395 911
## [132,] 2101 589 314 346 70 310
## [133,] 14903 2032 2479 576 955 328
## [134,] 9434 1042 1235 436 256 396
## [135,] 7388 1882 2174 720 47 537
## [136,] 6300 1289 2591 1170 199 326
## [137,] 4625 8579 7030 4575 2447 1542
## [138,] 3087 8080 8282 661 721 36
## [139,] 13537 4257 5034 155 249 3271
## [140,] 5387 4979 3343 825 637 929
## [141,] 17623 4280 7305 2279 960 2616
## [142,] 30379 13252 5189 321 51 1450
## [143,] 37036 7152 8253 2995 20 3
## [144,] 10405 1596 1096 8425 399 318
## [145,] 18827 3677 1988 118 516 201
## [146,] 22039 8384 34792 42 12591 4430
## [147,] 7769 1936 2177 926 73 520
## [148,] 9203 3373 2707 1286 1082 526
## [149,] 5924 584 542 4052 283 434
## [150,] 31812 1433 1651 800 113 1440
## [151,] 16225 1825 1765 853 170 1067
## [152,] 1289 3328 2022 531 255 1774
## [153,] 18840 1371 3135 3001 352 184
## [154,] 3463 9250 2368 779 302 1627
## [155,] 622 55 137 75 7 8
## [156,] 1989 10690 19460 233 11577 2153
## [157,] 3830 5291 14855 317 6694 3182
## [158,] 17773 1366 2474 3378 811 418
## [159,] 2861 6570 9618 930 4004 1682
## [160,] 355 7704 14682 398 8077 303
## [161,] 1725 3651 12822 824 4424 2157
## [162,] 12434 540 283 1092 3 2233
## [163,] 15177 2024 3810 2665 232 610
## [164,] 5531 15726 26870 2367 13726 446
## [165,] 5224 7603 8584 2540 3674 238
## [166,] 15615 12653 19858 4425 7108 2379
## [167,] 4822 6721 9170 993 4973 3637
## [168,] 2926 3195 3268 405 1680 693
## [169,] 5809 735 803 1393 79 429
## [170,] 5414 717 2155 2399 69 750
## [171,] 260 8675 13430 1116 7015 323
## [172,] 200 25862 19816 651 8773 6250
## [173,] 955 5479 6536 333 2840 707
## [174,] 514 7677 19805 937 9836 716
## [175,] 286 1208 5241 2515 153 1442
## [176,] 2343 7845 11874 52 4196 1697
## [177,] 45640 6958 6536 7368 1532 230
## [178,] 12759 7330 4533 1752 20 2631
## [179,] 11002 7075 4945 1152 120 395
## [180,] 3157 4888 2500 4477 273 2165
## [181,] 12356 6036 8887 402 1382 2794
## [182,] 112151 29627 18148 16745 4948 8550
## [183,] 694 8533 10518 443 6907 156
## [184,] 36847 43950 20170 36534 239 47943
## [185,] 327 918 4710 74 334 11
## [186,] 8170 6448 1139 2181 58 247
## [187,] 3009 521 854 3470 949 727
## [188,] 2438 8002 9819 6269 3459 3
## [189,] 8040 7639 11687 2758 6839 404
## [190,] 834 11577 11522 275 4027 1856
## [191,] 16936 6250 1981 7332 118 64
## [192,] 13624 295 1381 890 43 84
## [193,] 5509 1461 2251 547 187 409
## [194,] 180 3485 20292 959 5618 666
## [195,] 7107 1012 2974 806 355 1142
## [196,] 17023 5139 5230 7888 330 1755
## [197,] 30624 7209 4897 18711 763 2876
## [198,] 2427 7097 10391 1127 4314 1468
## [199,] 11686 2154 6824 3527 592 697
## [200,] 9670 2280 2112 520 402 347
## [201,] 3067 13240 23127 3941 9959 731
## [202,] 4484 14399 24708 3549 14235 1681
## [203,] 25203 11487 9490 5065 284 6854
## [204,] 583 685 2216 469 954 18
## [205,] 1956 891 5226 1383 5 1328
## [206,] 1107 11711 23596 955 9265 710
## [207,] 6373 780 950 878 288 285
## [208,] 2541 4737 6089 2946 5316 120
## [209,] 1537 3748 5838 1859 3381 806
## [210,] 5550 12729 16767 864 12420 797
## [211,] 18567 1895 1393 1801 244 2100
## [212,] 12119 28326 39694 4736 19410 2870
## [213,] 7291 1012 2062 1291 240 1775
## [214,] 3317 6602 6861 1329 3961 1215
## [215,] 2362 6551 11364 913 5957 791
## [216,] 2806 10765 15538 1374 5828 2388
## [217,] 2532 16599 36486 179 13308 674
## [218,] 18044 1475 2046 2532 130 1158
## [219,] 18 7504 15205 1285 4797 6372
## [220,] 4155 367 1390 2306 86 130
## [221,] 14755 899 1382 1765 56 749
## [222,] 5396 7503 10646 91 4167 239
## [223,] 5041 1115 2856 7496 256 375
## [224,] 2790 2527 5265 5612 788 1360
## [225,] 7274 659 1499 784 70 659
## [226,] 12680 3243 4157 660 761 786
## [227,] 20782 5921 9212 1759 2568 1553
## [228,] 4042 2204 1563 2286 263 689
## [229,] 1869 577 572 950 4762 203
## [230,] 8656 2746 2501 6845 694 980
## [231,] 11072 5989 5615 8321 955 2137
## [232,] 2344 10678 3828 1439 1566 490
## [233,] 25962 1780 3838 638 284 834
## [234,] 964 4984 3316 937 409 7
## [235,] 15603 2703 3833 4260 325 2563
## [236,] 1838 6380 2824 1218 1216 295
## [237,] 8635 820 3047 2312 415 225
## [238,] 18692 3838 593 4634 28 1215
## [239,] 7363 475 585 1112 72 216
## [240,] 47493 2567 3779 5243 828 2253
## [241,] 22096 3575 7041 11422 343 2564
## [242,] 24929 1801 2475 2216 412 1047
## [243,] 18226 659 2914 3752 586 578
## [244,] 11210 3576 5119 561 1682 2398
## [245,] 6202 7775 10817 1183 3143 1970
## [246,] 3062 6154 13916 230 8933 2784
## [247,] 8885 2428 1777 1777 430 610
## [248,] 13569 346 489 2077 44 659
## [249,] 15671 5279 2406 559 562 572
## [250,] 8040 3795 2070 6340 918 291
## [251,] 3191 1993 1799 1730 234 710
## [252,] 6134 23133 33586 6746 18594 5121
## [253,] 6623 1860 4740 7683 205 1693
## [254,] 29526 7961 16966 432 363 1391
## [255,] 10379 17972 4748 4686 1547 3265
## [256,] 31614 489 1495 3242 111 615
## [257,] 11092 5008 5249 453 392 373
## [258,] 8475 1931 1883 5004 3593 987
## [259,] 56083 4563 2124 6422 730 3321
## [260,] 53205 4959 7336 3012 967 818
## [261,] 9193 4885 2157 327 780 548
## [262,] 7858 1110 1094 6818 49 287
## [263,] 23257 1372 1677 982 429 655
## [264,] 2153 1115 6684 4324 2894 411
## [265,] 1073 9679 15445 61 5980 1265
## [266,] 5909 23527 13699 10155 830 3636
## [267,] 572 9763 22182 2221 4882 2563
## [268,] 20893 1222 2576 3975 737 3628
## [269,] 11908 8053 19847 1069 6374 698
## [270,] 15218 258 1138 2516 333 204
## [271,] 4720 1032 975 5500 197 56
## [272,] 2083 5007 1563 1120 147 1550
## [273,] 514 8323 6869 529 93 1040
## [274,] 36817 3045 1493 4802 210 1824
## [275,] 894 1703 1841 744 759 1153
## [276,] 680 1610 223 862 96 379
## [277,] 27901 3749 6964 4479 603 2503
## [278,] 9061 829 683 16919 621 139
## [279,] 11693 2317 2543 5845 274 1409
## [280,] 17360 6200 9694 1293 3620 1721
## [281,] 3366 2884 2431 977 167 1104
## [282,] 12238 7108 6235 1093 2328 2079
## [283,] 49063 3965 4252 5970 1041 1404
## [284,] 25767 3613 2013 10303 314 1384
## [285,] 68951 4411 12609 8692 751 2406
## [286,] 40254 640 3600 1042 436 18
## [287,] 7149 2247 1242 1619 1226 128
## [288,] 15354 2102 2828 8366 386 1027
## [289,] 16260 594 1296 848 445 258
## [290,] 42786 286 471 1388 32 22
## [291,] 2708 2160 2642 502 965 1522
## [292,] 6022 3354 3261 2507 212 686
## [293,] 2838 3086 4329 3838 825 1060
## [294,] 3996 11103 12469 902 5952 741
## [295,] 21273 2013 6550 909 811 1854
## [296,] 7588 1897 5234 417 2208 254
## [297,] 19087 1304 3643 3045 710 898
## [298,] 8090 3199 6986 1455 3712 531
## [299,] 6758 4560 9965 934 4538 1037
## [300,] 444 879 2060 264 290 259
## [301,] 16448 6243 6360 824 2662 2005
## [302,] 5283 13316 20399 1809 8752 172
## [303,] 2886 5302 9785 364 6236 555
## [304,] 2599 3688 13829 492 10069 59
## [305,] 161 7460 24773 617 11783 2410
## [306,] 243 12939 8852 799 3909 211
## [307,] 6468 12867 21570 1840 7558 1543
## [308,] 17327 2374 2842 1149 351 925
## [309,] 6987 1020 3007 416 257 656
## [310,] 918 20655 13567 1465 6846 806
## [311,] 7034 1492 2405 12569 299 1117
## [312,] 29635 2335 8280 3046 371 117
## [313,] 2137 3737 19172 1274 17120 142
## [314,] 9784 925 2405 4447 183 297
## [315,] 10617 1795 7647 1483 857 1233
## [316,] 1479 14982 11924 662 3891 3508
## [317,] 7127 1375 2201 2679 83 1059
## [318,] 1182 3088 6114 978 821 1637
## [319,] 11800 2713 3558 2121 706 51
## [320,] 9759 25071 17645 1128 12408 1625
## [321,] 1774 3696 2280 514 275 834
## [322,] 9155 1897 5167 2714 228 1113
## [323,] 15881 713 3315 3703 1470 229
## [324,] 13360 944 11593 915 1679 573
## [325,] 25977 3587 2464 2369 140 1092
## [326,] 32717 16784 13626 60869 1272 5609
## [327,] 4414 1610 1431 3498 387 834
## [328,] 542 899 1664 414 88 522
## [329,] 16933 2209 3389 7849 210 1534
## [330,] 5113 1486 4583 5127 492 739
## [331,] 9790 1786 5109 3570 182 1043
## [332,] 11223 14881 26839 1234 9606 1102
## [333,] 22321 3216 1447 2208 178 2602
## [334,] 8565 4980 67298 131 38102 1215
## [335,] 16823 928 2743 11559 332 3486
## [336,] 27082 6817 10790 1365 4111 2139
## [337,] 13970 1511 1330 650 146 778
## [338,] 9351 1347 2611 8170 442 868
## [339,] 3 333 7021 15601 15 550
## [340,] 2617 1188 5332 9584 573 1942
## [341,] 381 4025 9670 388 7271 1371
## [342,] 2320 5763 11238 767 5162 2158
## [343,] 255 5758 5923 349 4595 1328
## [344,] 1689 6964 26316 1456 15469 37
## [345,] 3043 1172 1763 2234 217 379
## [346,] 1198 2602 8335 402 3843 303
## [347,] 2771 6939 15541 2693 6600 1115
## [348,] 27380 7184 12311 2809 4621 1022
## [349,] 3428 2380 2028 1341 1184 665
## [350,] 5981 14641 20521 2005 12218 445
## [351,] 3521 1099 1997 1796 173 995
## [352,] 1210 10044 22294 1741 12638 3137
## [353,] 608 1106 1533 830 90 195
## [354,] 117 6264 21203 228 8682 1111
## [355,] 14039 7393 2548 6386 1333 2341
## [356,] 190 727 2012 245 184 127
## [357,] 22686 134 218 3157 9 548
## [358,] 37 1275 22272 137 6747 110
## [359,] 759 18664 1660 6114 536 4100
## [360,] 796 5878 2109 340 232 776
## [361,] 19746 2872 2006 2601 468 503
## [362,] 4734 607 864 1206 159 405
## [363,] 2121 1601 2453 560 179 712
## [364,] 4627 997 4438 191 1335 314
## [365,] 2615 873 1524 1103 514 468
## [366,] 4692 6128 8025 1619 4515 3105
## [367,] 9561 2217 1664 1173 222 447
## [368,] 3477 894 534 1457 252 342
## [369,] 22335 1196 2406 2046 101 558
## [370,] 6211 337 683 1089 41 296
## [371,] 39679 3944 4955 1364 523 2235
## [372,] 20105 1887 1939 8164 716 790
## [373,] 3884 3801 1641 876 397 4829
## [374,] 15076 6257 7398 1504 1916 3113
## [375,] 6338 2256 1668 1492 311 686
## [376,] 5841 1450 1162 597 476 70
## [377,] 3136 8630 13586 5641 4666 1426
## [378,] 38793 3154 2648 1034 96 1242
## [379,] 3225 3294 1902 282 68 1114
## [380,] 4048 5164 10391 130 813 179
## [381,] 28257 944 2146 3881 600 270
## [382,] 17770 4591 1617 9927 246 532
## [383,] 34454 7435 8469 2540 1711 2893
## [384,] 1821 1364 3450 4006 397 361
## [385,] 10683 21858 15400 3635 282 5120
## [386,] 11635 922 1614 2583 192 1068
## [387,] 1206 3620 2857 1945 353 967
## [388,] 20918 1916 1573 1960 231 961
## [389,] 9785 848 1172 1677 200 406
## [390,] 9385 1530 1422 3019 227 684
## [391,] 3352 1181 1328 5502 311 1000
## [392,] 2647 2761 2313 907 95 1827
## [393,] 518 4180 3600 659 122 654
## [394,] 23632 6730 3842 8620 385 819
## [395,] 12377 865 3204 1398 149 452
## [396,] 9602 1316 1263 2921 841 290
## [397,] 4515 11991 9345 2644 3378 2213
## [398,] 11535 1666 1428 6838 64 743
## [399,] 11442 1032 582 5390 74 247
## [400,] 9612 577 935 1601 469 375
## [401,] 4446 906 1238 3576 153 1014
## [402,] 27167 2801 2128 13223 92 1902
## [403,] 26539 4753 5091 220 10 340
## [404,] 25606 11006 4604 127 632 288
## [405,] 18073 4613 3444 4324 914 715
## [406,] 6884 1046 1167 2069 593 378
## [407,] 25066 5010 5026 9806 1092 960
## [408,] 7362 12844 18683 2854 7883 553
## [409,] 8257 3880 6407 1646 2730 344
## [410,] 8708 3634 6100 2349 2123 5137
## [411,] 6633 2096 4563 1389 1860 1892
## [412,] 2126 3289 3281 1535 235 4365
## [413,] 97 3605 12400 98 2970 62
## [414,] 4983 4859 6633 17866 912 2435
## [415,] 5969 1990 3417 5679 1135 290
## [416,] 7842 6046 8552 1691 3540 1874
## [417,] 4389 10940 10908 848 6728 993
## [418,] 5065 5499 11055 364 3485 1063
## [419,] 660 8494 18622 133 6740 776
## [420,] 8861 3783 2223 633 1580 1521
## [421,] 4456 5266 13227 25 6818 1393
## [422,] 17063 4847 9053 1031 3415 1784
## [423,] 26400 1377 4172 830 948 1218
## [424,] 17565 3686 4657 1059 1803 668
## [425,] 16980 2884 12232 874 3213 249
## [426,] 11243 2408 2593 15348 108 1886
## [427,] 13134 9347 14316 3141 5079 1894
## [428,] 31012 16687 5429 15082 439 1163
## [429,] 3047 5970 4910 2198 850 317
## [430,] 8607 1750 3580 47 84 2501
## [431,] 3097 4230 16483 575 241 2080
## [432,] 8533 5506 5160 13486 1377 1498
## [433,] 21117 1162 4754 269 1328 395
## [434,] 1982 3218 1493 1541 356 1449
## [435,] 16731 3922 7994 688 2371 838
## [436,] 29703 12051 16027 13135 182 2204
## [437,] 39228 1431 764 4510 93 2346
## [438,] 14531 15488 30243 437 14841 1867
## [439,] 10290 1981 2232 1038 168 2125
## [440,] 2787 1698 2510 65 477 52
predict(wholesale_pca)[,1]
## [1] -0.19707283 -0.45313294 -0.81180172 0.79342916 -0.11570147
## [6] 0.14370629 0.32567049 -0.15665440 0.48890741 -1.62027497
## [11] -0.66758413 0.92597350 -0.92658585 -0.82672223 -0.80858534
## [16] 0.93709140 -0.60479469 0.33914993 -0.29126066 0.29954840
## [21] 0.33682556 1.09654804 0.26619036 -4.58054505 -1.19755447
## [26] 0.15537156 1.03266607 1.09811094 -3.14687957 0.88052223
## [31] -0.05215116 0.69579690 0.98632753 0.41807632 1.02591988
## [36] -0.21643153 0.24158323 -0.97020398 -1.62332525 0.95272626
## [41] 0.08308879 0.25869103 -0.87588116 -2.00255094 -0.30164586
## [46] -2.83141245 -1.90336183 -9.41725404 -0.44041724 -3.63590895
## [51] 0.91517116 0.47041131 0.34153413 -0.75096260 1.02036283
## [56] 0.48573185 -4.63920836 -0.95925425 1.08902399 0.02055344
## [61] 0.20266611 -8.37149191 -0.04643766 -1.44256223 0.84129649
## [66] -5.88216805 0.42975520 -0.59711484 0.22115034 1.02170230
## [71] 0.84070633 -1.73915275 0.62067938 0.26682334 -0.04638691
## [76] 1.20012549 0.54017219 -2.77004981 1.12399443 0.65209963
## [81] 1.03868601 -1.10479248 -0.56696336 1.03054389 0.39812160
## [86] -12.68123458 -8.39266413 -0.92068706 1.01342557 0.44301966
## [91] 1.19321062 0.80614475 -5.24057761 0.52578694 -0.79761716
## [96] 0.71560919 0.24404605 1.32938626 1.32246301 1.02727861
## [101] -1.13082005 -1.34423210 -0.21246138 0.06820127 0.80468449
## [106] 0.94469735 -0.66901612 -1.47652662 -0.04077613 -1.70666698
## [111] 0.99983015 -1.37687414 0.68923179 0.90109151 1.05901888
## [116] 1.05586310 0.94497402 0.63888952 0.94868598 0.98250864
## [121] 0.96940760 1.00153477 1.28120984 -0.18913115 0.86596557
## [126] 0.40917867 1.01779186 -0.30277111 0.39288434 1.02620109
## [131] 1.00675513 1.30343896 0.95838681 1.18401500 1.07458712
## [136] 1.08937421 -0.11183011 0.20888553 0.47286002 0.67212442
## [141] 0.28796809 -0.02250288 0.34418432 1.07654549 0.93281684
## [146] -3.18443785 1.06717252 0.80824332 1.22430136 1.05447741
## [151] 1.04333128 0.84943798 1.02940017 0.39707127 1.38885601
## [156] -2.10534411 -0.94690511 0.99393880 -0.28531006 -1.03017136
## [161] -0.35485260 1.14689210 0.92036981 -3.05168162 -0.14994267
## [166] -1.80878413 -0.54851470 0.71052625 1.24301618 1.12716773
## [171] -0.90926104 -3.27135965 0.20685284 -1.58573375 0.83240063
## [176] -0.53378209 0.23300367 0.34523774 0.52247477 0.63766473
## [181] 0.01290303 -3.32956183 -0.68822721 -7.47744667 1.00703448
## [186] 0.81312626 1.11229463 -0.24041783 -0.72607631 -0.78285913
## [191] 0.74272114 1.27769586 1.09693599 -0.81285702 1.00169591
## [196] 0.45245343 0.08628883 -0.39085008 0.66997842 1.02565202
## [201] -2.23900996 -2.99546346 -0.68180673 1.10109815 0.89280368
## [206] -2.04834810 1.22289397 0.02999763 0.29338844 -2.07821189
## [211] 0.95666185 -5.65091274 1.01303835 -0.07733767 -0.54162222
## [216] -1.23239191 -3.65784251 1.03509689 -1.19058168 1.25137280
## [221] 1.16786662 -0.30619270 1.02353682 0.64173440 1.19242546
## [226] 0.74927539 -0.04166179 1.03747427 0.74782120 0.82806814
## [231] 0.25762310 0.14712185 0.92806057 0.77748264 0.67882658
## [236] 0.58424690 1.07019195 0.93984852 1.29676093 0.65211081
## [241] 0.35751675 0.96409594 1.02852505 0.42242573 -0.37409228
## [246] -1.17838892 0.99935781 1.26979462 0.74868436 0.81396957
## [251] 1.04468274 -5.00768849 0.74545878 -0.38605647 -0.70708219
## [256] 1.18411490 0.63210547 0.60371331 0.51724649 0.38236102
## [261] 0.77157492 1.16886889 1.08603962 0.50559973 -1.05801199
## [266] -1.65734964 -1.47739059 0.72868453 -1.21350291 1.23813362
## [271] 1.19514203 0.78067858 0.26602762 0.86878444 0.97282972
## [276] 1.22069804 0.38108645 1.07846333 0.87750350 -0.22439955
## [281] 0.92072808 0.04172049 0.56179348 0.77559110 -0.05666773
## [286] 1.07514112 0.99534417 0.87483219 1.19971862 1.33657531
## [291] 0.83674885 0.85316130 0.69360374 -0.93965965 0.59455930
## [296] 0.66171399 0.90049568 0.25180413 -0.16562608 1.15462330
## [301] 0.06749116 -1.87238584 -0.36075328 -0.89344120 -2.24170924
## [306] -0.57018410 -1.88935546 0.92559692 1.05503352 -1.82444685
## [311] 0.91380091 0.64646544 -2.05651935 1.10515579 0.58629339
## [316] -1.18632311 1.04565960 0.55882703 0.88204365 -3.11235419
## [321] 0.88439078 0.80386112 0.92745036 0.37271862 0.85971976
## [326] -1.78946833 1.05267151 1.17723864 0.81408444 0.85138951
## [331] 0.81990469 -2.55569469 0.81764691 -7.61379702 0.73733540
## [336] -0.43016311 1.12215088 0.95236916 0.77302224 0.67925139
## [341] -0.44952190 -0.49874907 -0.03297929 -2.53250139 1.13340753
## [346] 0.22596844 -0.94277386 -0.52623469 0.89883641 -2.40481023
## [351] 1.08068712 -2.45061408 1.19422964 -1.46109306 0.29654054
## [356] 1.19246382 1.30670647 -0.84837304 -0.53430822 0.74548879
## [361] 0.95060230 1.24298882 1.04927604 0.87486904 1.13722957
## [366] -0.34134077 1.06478454 1.23457189 1.09202865 1.29790056
## [371] 0.54728205 0.92861428 0.55848361 -0.01036762 1.02837629
## [376] 1.15932849 -0.77356526 0.88358086 0.93923945 0.27600519
## [381] 1.07810889 0.81131596 -0.12863861 0.98212572 -1.64808006
## [386] 1.10233193 0.82259230 1.04129188 1.19768522 1.09437876
## [391] 1.06891237 0.88438236 0.79981986 0.48759544 1.07628493
## [396] 1.08292394 -0.65441107 1.06672699 1.21812567 1.20418087
## [401] 1.12755720 0.78619937 0.70963764 0.21181784 0.65039342
## [406] 1.13695208 0.43799628 -1.67259278 0.36550163 0.05904374
## [411] 0.58114647 0.54871526 0.02754893 0.18022987 0.84472130
## [416] -0.15011103 -0.94319868 -0.17681577 -1.21247875 0.67045226
## [421] -0.70505273 -0.06490484 0.82591686 0.57180936 0.04046836
## [426] 0.76883248 -0.93848842 -0.43132555 0.51934102 0.83217183
## [431] -0.12732308 0.28430937 0.83664364 0.89763536 0.27267232
## [436] -0.78171970 1.00383404 -3.47543102 0.91187529 1.06427400
#The aboved two gives us the same thing. predict is a good function to know.
wholesale$Channel <- as.factor(wholesale$Channel)
out <- sapply(1:5, function(i){plot(wholesale$Channel,wholesale_pca$x[,i],xlab=paste("PC",i,sep=""),ylab="Channel")})
pairs(wholesale_pca$x[,1:5], ylim = c(-6,4),xlim = c(-6,4),panel=function(x,y,...){text(x,y,wholesale$Channel)})
# Better Ways to Visualize
library(factoextra)
## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
library(FactoMineR)
library(ggfortify)
library(psych)
##
## Attaching package: 'psych'
## The following objects are masked from 'package:ggplot2':
##
## %+%, alpha
## The following object is masked from 'package:car':
##
## logit
library(corrplot)
## corrplot 0.92 loaded
library(devtools)
## Loading required package: usethis
# Correlation
pairs.panels(wholesale[,-1],
gap = 0,
bg = c("red", "blue")[wholesale$Channel],
pch=21)
pairs.panels(wholesale_pca$x,
gap=0,
bg = c("red", "blue")[wholesale$Channel],
pch=21)
fviz_eig(wholesale_pca, addlabels = TRUE)
fviz_pca_var(wholesale_pca,col.var = "cos2",
gradient.cols = c("#FFCC00", "#CC9933", "#660033", "#330033"),
repel = TRUE)
fviz_pca_ind(wholesale_pca, col.ind = "cos2",
gradient.cols = c("#FFCC00", "#CC9933", "#660033", "#330033"),
repel = TRUE)
biplot(wholesale_pca)
autoplot(wholesale_pca,
data = wholesale[,-1],
loadings = TRUE,
labels = wholesale$Channel)
# Different PCA Method.
res.pca <- PCA(wholesale[,-1], graph = FALSE)
print(res.pca)
## **Results for the Principal Component Analysis (PCA)**
## The analysis was performed on 440 individuals, described by 6 variables
## *The results are available in the following objects:
##
## name description
## 1 "$eig" "eigenvalues"
## 2 "$var" "results for the variables"
## 3 "$var$coord" "coord. for the variables"
## 4 "$var$cor" "correlations variables - dimensions"
## 5 "$var$cos2" "cos2 for the variables"
## 6 "$var$contrib" "contributions of the variables"
## 7 "$ind" "results for the individuals"
## 8 "$ind$coord" "coord. for the individuals"
## 9 "$ind$cos2" "cos2 for the individuals"
## 10 "$ind$contrib" "contributions of the individuals"
## 11 "$call" "summary statistics"
## 12 "$call$centre" "mean of the variables"
## 13 "$call$ecart.type" "standard error of the variables"
## 14 "$call$row.w" "weights for the individuals"
## 15 "$call$col.w" "weights for the variables"
# Visualize and Interpret PCA using these functions
#get_eigenvalue(res.pca): Extract the eigenvalues/variances of principal components
#fviz_eig(res.pca): Visualize the eigenvalues
#get_pca_ind(res.pca), get_pca_var(res.pca): Extract the results for individuals and variables, respectively.
#fviz_pca_ind(res.pca), fviz_pca_var(res.pca): Visualize the results individuals and variables, respectively.
#fviz_pca_biplot(res.pca): Make a biplot of individuals and variables.
eig.val <- get_eigenvalue(res.pca)
eig.val
## eigenvalue variance.percent cumulative.variance.percent
## Dim.1 2.64497357 44.082893 44.08289
## Dim.2 1.70258397 28.376400 72.45929
## Dim.3 0.74006477 12.334413 84.79371
## Dim.4 0.56373023 9.395504 94.18921
## Dim.5 0.28567634 4.761272 98.95048
## Dim.6 0.06297111 1.049519 100.00000
fviz_eig(res.pca, addlabels = TRUE, ylim = c(0, 50))
var <- get_pca_var(res.pca)
#var$coord: coordinates of variables to create a scatter plot
#var$cos2: represents the quality of representation for variables on the factor map. It’s calculated as the squared coordinates: var.cos2 = var.coord * var.coord.
#var$contrib: contains the contributions (in percentage) of the variables to the principal components.
#The contribution of a variable (var) to a given principal component is (in percentage) : (var.cos2 * 100) / (total cos2 of the component).
var
## Principal Component Analysis Results for variables
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the variables"
## 2 "$cor" "Correlations between variables and dimensions"
## 3 "$cos2" "Cos2 for the variables"
## 4 "$contrib" "contributions of the variables"
# Coordinates
head(var$coord)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## Fresh 0.06974378 0.6888622 0.69876010 -0.17770820 0.02602031
## Milk 0.88654635 0.1085197 -0.05194998 -0.06546390 -0.44179588
## Grocery 0.94206631 -0.1906204 0.09323953 0.07957747 0.16836310
## Frozen 0.08324992 0.7976140 -0.15346028 0.57714209 0.01492942
## Detergents_Paper 0.89227411 -0.3330361 0.11716213 0.12894882 0.18153322
## Delicassen 0.40444082 0.6579050 -0.45069909 -0.41450107 0.16820333
# Cos2: quality on the factore map
head(var$cos2)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## Fresh 0.004864195 0.47453114 0.488265675 0.031580205 0.0006770567
## Milk 0.785964426 0.01177653 0.002698800 0.004285523 0.1951835958
## Grocery 0.887488938 0.03633613 0.008693611 0.006332574 0.0283461332
## Frozen 0.006930549 0.63618812 0.023550058 0.333092988 0.0002228875
## Detergents_Paper 0.796153084 0.11091307 0.013726964 0.016627799 0.0329543113
## Delicassen 0.163572380 0.43283898 0.203129666 0.171811138 0.0282923595
# Contributions to the principal components
head(var$contrib)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## Fresh 0.1839034 27.8712328 65.9760729 5.6020067 0.23700133
## Milk 29.7153981 0.6916858 0.3646708 0.7602081 68.32333158
## Grocery 33.5537923 2.1341756 1.1747094 1.1233341 9.92246429
## Frozen 0.2620272 37.3660348 3.1821617 59.0873033 0.07802099
## Detergents_Paper 30.1006064 6.5143964 1.8548328 2.9496021 11.53554083
## Delicassen 6.1842728 25.4224745 27.4475524 30.4775458 9.90364098
#The plot Below is also known as variable correlation plots. It shows the relationships between all variables. It can be interpreted as follow:
#Positively correlated variables are grouped together.
#Negatively correlated variables are positioned on opposite sides of the plot origin (opposed quadrants).
#The distance between variables and the origin measures the quality of the variables on the factor map.
#Variables that are away from the origin are well represented on the factor map.
# Correlation circle
fviz_pca_var(res.pca, col.var = "black")
# Quality of representation
corrplot(var$cos2, is.corr=FALSE)
# Total cos2 of variables on Dim.1 and Dim.2
#A high cos2 indicates a good representation of the variable on the principal component.
#In this case the variable is positioned close to the circumference of the correlation circle.
#A low cos2 indicates that the variable is not perfectly represented by the PCs.
#In this case the variable is close to the center of the circle.
fviz_cos2(res.pca, choice = "var", axes = 1:2)
fviz_pca_var(res.pca, col.var = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE # Avoid text overlapping
)
# Change the transparency by cos2 values
fviz_pca_var(res.pca, alpha.var = "cos2")
corrplot(var$contrib, is.corr=FALSE)
# Contributions of variables to PC1
fviz_contrib(res.pca, choice = "var", axes = 1, top = 10)
# Contributions of variables to PC2
fviz_contrib(res.pca, choice = "var", axes = 2, top = 10)
fviz_pca_var(res.pca, col.var = "contrib",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07")
)
fviz_pca_var(res.pca, alpha.var = "contrib")
fviz_pca_ind(res.pca,
geom.ind = "point", # show points only (nbut not "text")
col.ind = wholesale$Channel, # color by groups
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
addEllipses = TRUE, # Concentration ellipses
legend.title = "Groups"
)
# Description of PC
res.desc <- dimdesc(res.pca, axes = c(1,2,3,4,5), proba = 0.05)
# Description of dimension 1
res.desc$Dim.1
##
## Link between the variable and the continuous variables (R-square)
## =================================================================================
## correlation p.value
## Grocery 0.9420663 6.584197e-210
## Detergents_Paper 0.8922741 2.332450e-153
## Milk 0.8865463 1.021905e-148
## Delicassen 0.4044408 9.572010e-19
res.desc$Dim.2
##
## Link between the variable and the continuous variables (R-square)
## =================================================================================
## correlation p.value
## Frozen 0.7976140 3.240676e-98
## Fresh 0.6888622 3.479571e-63
## Delicassen 0.6579050 6.655870e-56
## Milk 0.1085197 2.281127e-02
## Grocery -0.1906204 5.720097e-05
## Detergents_Paper -0.3330361 7.407426e-13
res.desc$Dim.3
##
## Link between the variable and the continuous variables (R-square)
## =================================================================================
## correlation p.value
## Fresh 0.6987601 1.038376e-65
## Detergents_Paper 0.1171621 1.392869e-02
## Frozen -0.1534603 1.242240e-03
## Delicassen -0.4506991 2.124105e-23
res.desc$Dim.4
##
## Link between the variable and the continuous variables (R-square)
## =================================================================================
## correlation p.value
## Frozen 0.5771421 1.940954e-40
## Detergents_Paper 0.1289488 6.759315e-03
## Fresh -0.1777082 1.790336e-04
## Delicassen -0.4145011 1.069376e-19
res.desc$Dim.5
##
## Link between the variable and the continuous variables (R-square)
## =================================================================================
## correlation p.value
## Detergents_Paper 0.1815332 1.287171e-04
## Grocery 0.1683631 3.897641e-04
## Delicassen 0.1682033 3.948465e-04
## Milk -0.4417959 1.902645e-22
# Graph of Indiviuals
ind <- get_pca_ind(res.pca)
ind
## Principal Component Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"
## Principal Component Analysis Results for individuals
## ===================================================
## Name Description
## 1 "$coord" "Coordinates for the individuals"
## 2 "$cos2" "Cos2 for the individuals"
## 3 "$contrib" "contributions of the individuals"
#To get access to the different components, use this:
# Coordinates of individuals
head(ind$coord)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## 1 0.1932905 -0.3051000 0.14087845 -0.4864315 -0.4952815
## 2 0.4344199 -0.3284126 -0.31900662 -0.1788304 -0.3655793
## 3 0.8111432 0.8150957 -1.52341562 -1.2540815 0.3790535
## 4 -0.7786478 0.6527537 -0.16301227 0.3800601 0.2761376
## 5 0.1662873 1.2714337 -0.06627939 -0.8262267 0.3942107
## 6 -0.1561699 -0.2951410 -0.14761194 -0.4182883 -0.4794549
# Quality of individuals
head(ind$cos2)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## 1 0.05909079 0.1472254 0.031389739 0.37423296 0.38797412
## 2 0.33287156 0.1902379 0.179496780 0.05640788 0.23573307
## 3 0.12102385 0.1222062 0.426886756 0.28928601 0.02642877
## 4 0.47243428 0.3320152 0.020706173 0.11255473 0.05941693
## 5 0.01111679 0.6499033 0.001766112 0.27444781 0.06247669
## 6 0.04507824 0.1610020 0.040273103 0.32338772 0.42488124
# Contributions of individuals
head(ind$contrib)
## Dim.1 Dim.2 Dim.3 Dim.4 Dim.5
## 1 0.003210312 0.01242576 0.006094902 0.09539365 0.19515389
## 2 0.016216062 0.01439721 0.031251939 0.01289313 0.10632521
## 3 0.056535480 0.08868619 0.712712536 0.63405591 0.11430734
## 4 0.052096452 0.05687711 0.008160527 0.05823452 0.06066302
## 5 0.002375986 0.21578747 0.001349070 0.27521650 0.12363168
## 6 0.002095660 0.01162781 0.006691455 0.07053870 0.18288096
fviz_pca_ind(res.pca)
fviz_pca_ind(res.pca, col.ind = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE # Avoid text overlapping (slow if many points)
)
fviz_pca_ind(res.pca, pointsize = "cos2",
pointshape = 21, fill = "#E7B800",
repel = TRUE # Avoid text overlapping (slow if many points)
)
fviz_pca_ind(res.pca, col.ind = "cos2", pointsize = "cos2",
gradient.cols = c("#00AFBB", "#E7B800", "#FC4E07"),
repel = TRUE # Avoid text overlapping (slow if many points)
)
fviz_cos2(res.pca, choice = "ind")
# Total contribution on PC1 and PC2
fviz_contrib(res.pca, choice = "ind", axes = 1:2)
# Create a random continuous variable of length 23,
# Same length as the number of active individuals in the PCA
set.seed(123)
my.cont.var <- rnorm(49)
# Color individuals by the continuous variable
fviz_pca_ind(res.pca,
geom.ind = "point", # show points only (nbut not "text")
col.ind = wholesale$Channel, # color by groups
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
addEllipses = TRUE, # Concentration ellipses
legend.title = "Groups"
)
fviz_pca_ind(res.pca, geom.ind = "point", col.ind = wholesale$Channel,
palette = c("#00AFBB", "#E7B800", "#FC4E07"),
addEllipses = TRUE, ellipse.type = "confidence",
legend.title = "Groups"
)
fviz_pca_ind(res.pca,
label = "none", # hide individual labels
habillage = wholesale$Channel, # color by groups
addEllipses = TRUE, # Concentration ellipses
palette = "jco"
)
fviz_pca_var(res.pca, geom.var = c("point", "text"))
# Show individuals text labels only
fviz_pca_ind(res.pca, geom.ind = "text")
# Change the size of arrows an labels
fviz_pca_var(res.pca, arrowsize = 1, labelsize = 5,
repel = TRUE)
# Change points size, shape and fill color
# Change labelsize
fviz_pca_ind(res.pca,
pointsize = 3, pointshape = 21, fill = "lightblue",
labelsize = 5, repel = TRUE)
fviz_pca_ind(res.pca,
geom.ind = "point", # show points only (but not "text")
group.ind = wholesale$Channel, # color by groups
legend.title = "Groups",
mean.point = FALSE)
fviz_pca_ind(res.pca,
geom.ind = "point", # show points only (but not "text")
group.ind = wholesale$Channel, # color by groups
legend.title = "Groups",
mean.point = TRUE)
fviz_pca_var(res.pca, axes.linetype = "blank")
ind.p <- fviz_pca_ind(res.pca, geom = "point", col.ind = wholesale$Channel)
ggpubr::ggpar(ind.p,
title = "Principal Component Analysis",
subtitle = "Wholesale Dataset",
xlab = "PC1", ylab = "PC2",
legend.title = "Channel", legend.position = "top",
ggtheme = theme_gray(), palette = "jco"
)
fviz_pca_biplot(res.pca, repel = TRUE,col.ind = wholesale$Channel,
col.var = "#2E9FDF", # Variables color
)
fviz_pca_biplot(res.pca,
col.ind = wholesale$Channel, palette = "jco",
addEllipses = TRUE, label = "var",
col.var = "black", repel = TRUE,
legend.title = "Channel")
fviz_pca_biplot(res.pca,
# Fill individuals by groups
geom.ind = "point",
pointshape = 21,
pointsize = 2.5,
fill.ind = wholesale$Channel,
col.ind = "black",
# Color variable by groups
legend.title = list(fill = "Channel", color = "Clusters"),
repel = TRUE # Avoid label overplotting
)+
ggpubr::fill_palette("jco")+ # Indiviual fill color
ggpubr::color_palette("npg") # Variable colors
fviz_pca_biplot(res.pca,
# Individuals
geom.ind = "point",
fill.ind = wholesale$Channel, col.ind = "black",
pointshape = 21, pointsize = 2,
palette = "jco",
addEllipses = TRUE,
# Variables
alpha.var ="contrib", col.var = "contrib",
gradient.cols = "RdYlBu",
legend.title = list(fill = "Channel", color = "Contrib",
alpha = "Contrib")
)
